Communication error alerting in an epilepsy monitoring system

ABSTRACT

Systems and methods for monitoring neurological signals in a patient are provided. The system includes: an implantable sensor adapted to collect neurological signals; an implantable assembly configured to sample the neurological signals collected by the sensor; and a rechargeable communication device external to the patient&#39;s body, said communication device configured to wirelessly communicate with the implantable assembly and to transmit a communication error alert to a caregiver advisory device in the event of a communication error between the implantable assembly and the communication device.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of pending U.S. patentapplication Ser. No. 12/020,507, filed Jan. 25, 2008, which claimsbenefit of U.S. Provisional Patent Application No. 60/897,551, filedJan. 25, 2007, the disclosures of which are incorporated by referenceherein in their entirety.

BACKGROUND OF THE INVENTION

The present invention relates generally to systems and methods forsampling and processing one or more physiological signals from asubject. More specifically, the present invention relates to monitoringof one or more neurological signals from a subject to determine asubject's susceptibility to a neurological event, communicating thesubject's susceptibility to the subject, reducing a severity of seizuresand/or preventing seizures. The invention also relates to continuouslystoring neurological signals from a subject to train algorithms todetermine a subject's susceptibility for having a seizure.

Epilepsy is a neurological disorder of the brain characterized bychronic, recurring seizures. Seizures are a result of uncontrolleddischarges of electrical activity in the brain. A seizure typicallymanifests itself as sudden, involuntary, disruptive, and oftendestructive sensory, motor, and cognitive phenomena. Seizures arefrequently associated with physical harm to the body (e.g., tonguebiting, limb breakage, and burns), a complete loss of consciousness, andincontinence. A typical seizure, for example, might begin as spontaneousshaking of an arm or leg and progress over seconds or minutes torhythmic movement of the entire body, loss of attention, loss ofconsciousness, and voiding of urine or stool.

A single seizure most often does not cause significant morbidity ormortality, but severe or recurring seizures (epilepsy) results in majormedical, social, and economic consequences. Epilepsy is most oftendiagnosed in children and young adults, making the long-term medical andsocietal burden severe for this population of subjects. People withuncontrolled epilepsy are often significantly limited in their abilityto work in many industries and usually cannot legally drive anautomobile. An uncommon, but potentially lethal form of seizure iscalled status epilepticus, in which a seizure continues for more than 30minutes. This continuous seizure activity may lead to permanent braindamage, and can be lethal if untreated.

While the exact cause of epilepsy is often uncertain, epilepsy canresult from head trauma (such as from a car accident or a fall),infection (such as meningitis), stroke, or from neoplastic, vascular ordevelopmental abnormalities of the brain. Approximately 70% of epilepticsubjects, especially most forms that are resistant to treatment (i.e.,refractory), are idiopathic or of unknown causes, and is generallypresumed to be an inherited genetic disorder.

Demographic studies have estimated the prevalence of epilepsy atapproximately 1% of the population, or approximately 2.5 millionindividuals in the United States alone. In order to assess possiblecauses and to guide treatment, epileptologists (both neurologists andneurosurgeons) typically evaluate subjects with seizures with brain waveelectrical analysis and imaging studies, such as magnetic resonanceimaging (MRI).

While there is no known cure for epilepsy, chronic usage ofanticonvulsant and antiepileptic medications can control seizures inmost people. For most cases of epilepsy, the disease is chronic andrequires chronic medications for treatment. The anticonvulsant andantiepileptic medications do not actually correct the underlyingconditions that cause seizures. Instead, the anticonvulsant andantiepileptic medications manage the subject's epilepsy by reducing thefrequency of seizures. There are a variety of classes of antiepilepticdrugs (AEDs), each acting by a distinct mechanism or set of mechanisms.

AEDs generally suppress neural activity by a variety of mechanisms,including altering the activity of cell membrane ion channels and thesusceptibility of action potentials or bursts of action potentials to begenerated. These desired therapeutic effects are often accompanied bythe undesired side effect of sedation, nausea, dizziness, etc. Some ofthe fast acting AEDs, such as benzodiazepine, are also primarily used assedatives. Other medications have significant non-neurological sideeffects, such as gingival hyperplasia, a cosmetically undesirableovergrowth of the gums, and/or a thickening of the skull, as occurs withphenytoin. Furthermore, some AED are inappropriate for women of childbearing age due to the potential for causing severe birth defects.

An estimated 70% of subjects will respond favorably to their first AEDmonotherapy and no further medications will be required. However, forthe remaining 30% of the subjects, their first AED will fail to fullycontrol their seizures and they will be prescribed a second AED—often inaddition to the first—even if the first AED does not stop or change apattern or frequency of the subject's seizures. For those that fail thesecond AED, a third AED will be tried, and so on. Subjects who fail togain control of their seizures through the use of AEDs are commonlyreferred to as “medically refractory.” This creates a scenario in which750,000 subjects or more in the United States have uncontrolledepilepsy. These medically refractory subjects account for 80% of the$12.5 billion in indirect and direct costs that are attributable toepilepsy in the United States.

A major challenge for physicians treating epileptic subjects is gaininga clear view of the effect of a medication or incremental medications.Presently, the standard metric for determining efficacy of themedication is for the subject or for the subject's caregiver to keep adiary of seizure activity. However, it is well recognized that suchself-reporting is often of poor quality because subjects often do notrealize when they have had a seizure, or fail to accurately recordseizures.

If a subject is refractory to treatment with chronic usage ofmedications, surgical treatment options may be considered. If anidentifiable seizure focus is found in an accessible region of thebrain, which does not involve “eloquent cortex” or other criticalregions of the brain, then resection is considered. If no focus isidentifiable, or there are multiple foci, or the foci are in surgicallyinaccessible regions or involve eloquent cortex, then surgery is lesslikely to be successful or may not be indicated. Surgery is effective inmore than half of the cases, in which it is indicated, but it is notwithout risk, and it is irreversible. Because of the inherent surgicalrisks and the potentially significant neurological sequelae fromresective procedures, many subjects or their parents decline thistherapeutic modality.

Some non-resective functional procedures, such as corpus callosotomy andsubpial transection, sever white matter pathways without removingtissue. The objective of these surgical procedures is to interruptpathways that mediate spread of seizure activity. These functionaldisconnection procedures can also be quite invasive and may be lesseffective than resection.

An alternative treatment for epilepsy that has demonstrated some utilityis open loop Vagus Nerve Stimulation (VNS). This is a reversibleprocedure which introduces an electronic device which employs a pulsegenerator and an electrode to alter neural activity. The vagus nerve isa major nerve pathway that emanates from the brainstem and passesthrough the neck to control visceral function in the thorax and abdomen.VNS uses open looped, intermittent stimulation of the left vagus nervein the neck in an attempt to reduce the frequency and intensity ofseizures. See Fisher et al., “Reassessment: Vagus nerve stimulation forepilepsy, A report of the Therapeutics and Technology AssessmentSubcommittee of the American Academy of Neurology,” Neurology 1999;53:666-669. While not highly effective, it has been estimated that VNSreduces seizures by an average of approximately 30-50% in about 30-50%of subjects who are implanted with the device. Unfortunately, a vastmajority of the subjects who are outfitted with the Cyberonics® VNSdevice still suffer from un-forewarned seizures and many subjects obtainno benefit whatsoever.

Another recent alternative electrical stimulation therapy for thetreatment of epilepsy is deep brain stimulation (DBS). Open-loop deepbrain stimulation has been attempted at several anatomical target sites,including the anterior nucleus of the thalamus, the centromedian nucleusof the thalamus, and the hippocampus. The results have shown somepotential to reduce seizure frequency, but the efficacy leaves much roomfor improvement.

Another type of electrical stimulation therapy for the treatmentepilepsy has been proposed by NeuroPace, Inc., in which an implanteddevice is designed to detect abnormal electrical activity in the brainand respond by delivering electrical stimulation to the brain.

There have also been a number of proposals described in the patentliterature regarding the use of predictive algorithms that purportedlycan predict the onset of a seizure. When the predictive algorithmpredicts the onset of a seizure, some type of warning is provided to thesubject regarding the oncoming seizure or some sort of therapy isinitiated. For example, see U.S. Pat. No. 3,863,625 to Viglione, U.S.Pat. No. 5,995,868 to Dorfmeister/Osorio, and U.S. Pat. No. 6,658,287 toLitt et al., the complete disclosures of which are incorporated hereinby reference, describe a variety of proposed seizure prediction systems.However, to date, none of the proposed seizure prediction systems haveshown statistically significant results.

While most seizures are short-lasting events that last only a fewminutes, the seemingly random nature of the occurrence of seizures iswhat overshadows and destroys a subject's quality of life.

SUMMARY

Systems and methods for monitoring neurological signals in a patient areprovided. The system includes: an implantable sensor adapted to collectneurological signals; an implantable assembly configured to sample theneurological signals collected by the sensor; and a rechargeablecommunication device external to the patient's body, said communicationdevice configured to wirelessly communicate with the implantableassembly and to transmit a communication error alert to a caregiveradvisory device in the event of a communication error between theimplantable assembly and the communication device.

Also provided are methods and systems for sampling one or morephysiological signals from the subject and processing such physiologicalsignal(s) to monitor a subject's susceptibility or for a futureneurological event. Such systems may also be adapted to provide anindication to the subject of their susceptibility for the neurologicalevent, such as a warning or instruction, automatically initiate deliveryof therapy to the subject, or allow or instruct the subject or acaregiver to administer a therapy prior to the onset of the seizure.

In preferred embodiments, the present invention is for managingepilepsy. Managing epilepsy includes the prevention or reduction of theoccurrence of epileptic seizures and/or mitigating their effects, aswell as alerting a subject when their susceptibility for having aseizure has been determined to be low. The method of preventing anepileptic seizure comprises characterizing a subject's susceptibility orsusceptibility for a future seizure, and upon the determination that thesubject has an elevated susceptibility for the seizure, communicating tothe subject and/or a health care provider a warning or a therapyrecommendation and/or initiating a therapy.

In one embodiment, the present invention provides ambulatory datacollection systems and methods. The data collection systems of thepresent invention typically include one or more electrodes for samplingone or more physiological signals from the subject. In some embodiments,it may be desirable to include microelectrodes. In preferred embodiment,the physiological signals include signals that are indicative of neuralactivity in at least one portion of the brain, such as intracranial EEG(“iEEG” or “ECoG”), EEG, or a combination thereof. The electrodes may beintracranial electrodes (e.g., epidural, subdural, depth electrodes),extracranial electrodes (e.g., spike or bone screw electrodes,subcutaneous electrodes, scalp electrodes, dense array (256 channels)electrodes, etc.), or a combination thereof. While it is preferred tomonitor signals directly from the brain, it may also be desirable tomonitor brain activity using sphlenoidal electrodes, foramen ovaleelectrodes, intravascular electrodes, peripheral nerve electrodes,cranial nerve electrodes, or the like. While the remaining disclosurefocuses on intracranial electrodes, it should be appreciated that anytype of electrodes may be used to sample signals from the subject.

The one or more electrodes are typically in communication with animplanted assembly. The one or more electrodes may communicate with theimplanted assembly (or directly with the external assembly as describedbelow) with a wireless link, a wired link, or both. The implantedassembly is typically configured to facilitate transmission of a datasignal that is representative of the one or more sampled physiologicalsignals. The implanted assembly may be in wireless communication with anexternal assembly using any type of known uni-directional orbi-directional wireless link. Transmission of data and/or controlsignals between implantable assembly and the external assembly istypically carried out through a radiofrequency link, but may also becarried out through telemetry, magnetic induction, electromagnetic link,Bluetooth® link, Zigbee link, sonic link, optical link, other types ofconventional wireless links, or combinations thereof.

In one embodiment, the external assembly will typically be configured toestablish a one-way or two-way communication link with the implantedassembly using conventional telemetry handshaking protocols. Theexternal assembly may allow the subject (or the subject's physician) toadjust parameters of the sampling of the physiological signal—such asadjusting the sampling rate, the data transmission rate, errorcorrection, sampled channels, signal conditioning parameters (gain,filtering bandwidth, etc.), the type of data that is stored, or thelike. In some embodiments, the implanted assembly will transmit a datasignal that includes raw or processed physiological signal (e.g.,intracranial EEG, EEG, etc.), one or more features that are extractedfrom the one or more signals, a signal that is indicative of acommunication that is provided to the subject (e.g., warning, therapyrecommendation, etc.) or a combination thereof.

At least one of the implanted assembly and external assembly may have amemory sub-system for storing data that is representative of the one ormore physiological signals that are sampled with the one or moreelectrodes. In preferred embodiments, the data is stored in the memorysub-system of the external assembly. The data stored in the memorysub-system of the external assembly may thereafter be transferred to aFLASH drive, hard drive, a local computer, or to a remote server orcomputer system through a network connection (e.g., local area network(LAN), wide area network (WAN), the Internet, or the like). Preferably,the data will be transmitted to the subject's physician or computerstation that is running software that can analyze the subject'sphysiological signals.

In some embodiments, at least one of the implanted assembly and externalassembly will include one or more algorithms for analyzing the sampledphysiological signal in real time. Such algorithms may be used as aseizure advisory system that is configured to measure the subject'ssusceptibility for having a neurological symptom. The systems of thepresent invention will comprise similar elements as the data collectionsystem described above to facilitate sampling of EEG signals (and/orother physiological signals) from the subject that are indicative of thesubject's susceptibility to seizure. The EEG signals may be analyzed byone or more analysis algorithms to determine when a subject is in anictal state, a pro-ictal state or a contra-ictal state. An “ictal state”is used herein to refer to a seizure. The term “pro-ictal” is usedherein to refer to a neurological state or condition characterized by anincreased likelihood or higher susceptibility of transitioning to anictal state. The term “contra-ictal” is used herein to refer to aneurological state or condition characterized by a low likelihood orsusceptibility of transitioning to an ictal state and/or a pro-ictalstate within a predetermined period of time. A more complete descriptionof pro-ictal, contra-ictal and ictal states are described in co-pendingand commonly owned patent application Ser. No. 12/020,450, filed Jan.25, 2008, to Snyder et al., entitled “Systems and Methods forIdentifying a Contra-ictal Condition in a Subject,” the completedisclosure of which is incorporated herein by reference.

In one embodiment, a subject's susceptibility for a seizure can beestimated or derived from a neural condition which can be characterizedas a point along a single or multi-variable state space continuum. Theterm “neural state” is used herein to generally refer to calculationresults or indices that are reflective of the state of the subject'sneural system, but does not necessarily constitute a complete orcomprehensive accounting of the subject's total neurological condition.The estimation and characterization of “neural state” may be based onone or more subject dependent parameters from the brain, such aselectrical signals from the brain, including but not limited toelectroencephalogram signals “EEG” and electrocorticogram signals “ECoG”or intracranial EEG (referred to herein collectively as EEG″), braintemperature, blood flow in the brain, concentration of AEDs in the brainor blood, etc.), heart rate, respiratory rate, chemical concentrations,etc.

The algorithms may analyze the sampled EEG signals in the implantedassembly, in the external assembly, or a portion of the advisoryalgorithm may be in both the implanted assembly and the externalassembly. If the seizure advisory algorithm determines that the subjecthas entered a pro-ictal condition, the external assembly may be used toprovide a warning, instruction, or other output to the subject thatinforms them of their transitioning from an inter-ictal or normalcondition to the pro-ictal condition. The output from the externalassembly may be visual, audio, tactile (e.g., vibratory), or somecombination thereof. Such outputs from the external assembly may allowthe user to make themselves safe (e.g., stop cooking, pull to the sideof the road when driving, lie down, etc.) prior to the onset of theactual seizure or allow the subject to take an acute dosage of an AED toprevent or mitigate the seizure. Most importantly, the subject's will nolonger be surprised by the seizures and will have more control overtheir life.

Such algorithms may also be used to provide insight to the subject andthe subject's physician regarding the subject's specific seizuretriggers. For example, if the subject's susceptibility to a seizureincreases (and a warning is given) every time the subject intakesalcohol or a specific food, is sleep deprived, or is subject to acertain stimulus, the subject may be able to learn which triggers toavoid. Consequently, such seizure advisory systems will be able toprovide quantifiable data to the subject and their physician regardingthe subject-specific seizure triggers.

The seizure detection algorithm(s) may be used to detect theelectrographic seizure onset and provide a seizure warning to thesubject (or a care giver) just prior to the clinical manifestation ofthe seizure. Such a warning may or may not be sufficient to allow thesubject to stop the seizure from occurring, but at a minimum, thewarning will provide the subject or caregiver many seconds (or minutes)prior to the onset of the clinical seizure and allow the subject and/orcaregiver to make the subject safe.

The systems described herein can also include an alert that isconfigured to indicate that there is a communication error between theimplanted assembly and the external assembly. The alert can be disposedeither in the internal assembly or in the external assembly. The alertcan be a visible alert, an audible alert, a tactile alert, or anycombination thereof.

The communication error can be a single type of communication error, orit can be a combination of different types of communication errors. Forexample, the communication error can be that the external assembly isout of communication range with the implanted assembly such that theexternal assembly is not receiving a data signal from the implanteddevice. The communication error can be that the external assembly is outof communication range with the implanted assembly for a predeterminedamount of time. The communication error can be that the externalassembly not receiving the data signal at an expected time or within anexpected period of time. The external assembly can be configured toexpect to receive a substantially continuous data signal, or theexternal assembly can be programmed to expect to receive a data signalperiodically. The communication error can be that there is a gap in adata signal communication stream, such as missing packets of data in anumbered sequence of packets. The communication error can also be a dataformatting error, such as an invalid cyclic redundancy. If the systemdetects a communication error an alert will be activated to indicatethere is a communication error.

The systems that provide an alert when there is a communication errorbetween the implanted assembly and the external assembly can alsoinclude an input on the external assembly that allows the subject todeactivate an alert function when the subject has a low likelihood oftransitioning into the seizure condition, such as a contra-ictalcondition. An alarm deactivation period can be less than a time periodin which the subject is unlikely to transition into the seizurecondition. In one example, the deactivation period is 45 minutes and thetime period in which the subject is unlikely to transition into theseizure condition is 60 minutes. The deactivation period can beadjustable by the subject up to a maximum time period that does notexceed the time period in which the subject is unlikely to transitioninto the seizure condition.

Another aspect of the invention is a seizure advisory device. Theseizure advisory device includes a user interface that comprises anindicator that indicates if the subject is at a low susceptibility to aseizure or a high susceptibility to a seizure. The seizure advisorydevice also includes an alert that is configured to provide anindication, such as an audible output, to the subject if the seizureadvisory device is out of communication range with an implantabletelemetry unit and is unable to accurately communicate the subject'ssusceptibility to the seizure.

One aspect of the invention is a method of activating an alert whenthere is a communication error between an implantable device and adevice external to a subject. The method includes sampling a brainactivity signal from a subject, transmitting a data signal indicative ofthe sampled brain activity signal from an implanted assembly to anexternal assembly outside of the subject, and activating an alert whenthere is a communication error between the implanted assembly and theexternal assembly. The method can include storing the data signal in theimplanted assembly if there is a communication error, as well asattempting to retransmit the data signal after the error is detected.

One aspect of the invention is a method of informing a subject when aseizure advisory device is out of communication range with animplantable device. The method includes receiving a transcutaneouslytransmitted data signal indicative of the sampled brain activity signalfrom an implanted device and activating an alert when an expected datasignal transmitted from the implanted device is not received by theseizure advisory device. The seizure advisory device can be configuredto analyze the data signal to estimate the subject's susceptibility to aseizure. Alternatively, the implanted device is configured to analyzethe data signal to estimate the subject's susceptibility to a seizureand the seizure advisory device is configured to communicate theestimated susceptibility to the subject. The data signal can betransmitted substantially continuously and comprises substantiallyreal-time sampled brain activity signals.

The seizure advisory systems of the present invention may be used inconjunction with a therapy that may prevent the seizure from occurring,reduce the severity of the oncoming seizure, reduce the duration of theoncoming seizure, or the like. The therapy may be initiated in a closedloop within the system, or the therapy may be manually initiated by thesubject or caregiver.

Depending on the level of the subject's susceptibility for a seizure,the output provided to the subject may take a variety of differentforms. Some embodiments will provide an output to the subject thatcauses the subject to take an acute dosage of a pharmacological agent(e.g., neuro-suppressant, sedative such as a rapid onset benzodiazepine,AED or anticonvulsant, or other medication which exhibits seizureprevention effects). The advisory algorithm(s) may be used tocharacterize the subject's susceptibility for a future seizure. If theadvisory algorithm determines that the subject is at an increased orelevated susceptibility for a future seizure, the system may provide anoutput to the subject and/or caregiver that facilitates the subject totake or the caregiver to provide an acute dosage of a pharmacologicalagent (such as an AED) to prevent the occurrence of the seizure orreduce the magnitude or duration of the seizure.

As used herein, the term “anti-epileptic drug” or “AED” generallyencompasses pharmacological agents that reduce the frequency orsusceptibility of a seizure. There are many drug classes that comprisethe set of AEDs, and many different mechanisms of action arerepresented. For example, some medications are believed to increase theseizure threshold, thereby making the brain less likely to initiate aseizure. Other medications retard the spread of neural bursting activityand tend to prevent the propagation or spread of seizure activity. SomeAEDs, such as the benzodiazepines, act via the GABA receptor andglobally suppress neural activity. However, other AEDs may act bymodulating a neuronal calcium channel, a neuronal potassium channel, aneuronal NMDA channel, a neuronal AMPA channel, a neuronal metabotropictype channel, a neuronal sodium channel, and/or a neuronal kainitechannel.

Unlike conventional anti-epileptic drug treatments, which provide for an“open loop” chronic regimen of pharmacological agents, the presentinvention is able to manage seizures acutely while substantiallyoptimizing the intake of the pharmacological agent by having the subjectto take a pharmacological agent only when it is determined that thesubject has transitioned to a higher susceptibility to a seizure, e.g.,to a pro-ictal condition. Furthermore, with this new paradigm of seizureprevention, the present invention provides a new indication forpharmacotherapy. This new indication is served by several existingmedications, including AEDs, given at doses which are sub-therapeutic totheir previously known indications, such as acute AED administration forseizure termination or status epilepticus. Since this new indication isserved by a new and much lower dosing regimen and consequently a newtherapeutic window, the present invention is able to provide acorrespondingly new and substantially reduced side effect profile andmay reduce or eliminate tolerance effects of the AED. For example, thepresent invention allows the use of dosages that are lower thanFDA-approved dosages for the various anti-epileptic agents. This dosingmay be about 5% to about 95% lower than the FDA-recommended dose for thedrug, and preferably at or below 90% of the FDA-recommended dose, andmost preferably below about 50% of the FDA-recommended dose. But as canbe appreciated, if the measured signals indicate a high susceptibilityfor a seizure, the methods and systems of the present invention mayrecommend taking an FDA or a higher than FDA approved dose of the AED toprevent the seizure. Such a paradigm has valuable application forsubjects in which side effects of AEDs are problematic, particularsedation in general and teratogenicity in pregnant women or risk ofteratogenicity in all women of child bearing age. A more completedescription of using acute dosages of AEDs with a seizure advisorysystem is described in commonly owned U.S. patent application Ser. Nos.11/321,897, 11/321,898, and 11/322,150 (all filed Dec. 28, 2005), thecomplete disclosures of which are incorporated herein by reference.

In another embodiment, the present invention provides a system thatcomprises an advisory algorithm that may be used to modify or alter thescheduling and/or dosing of a chronically prescribed pharmacologicalagent, such as an AED, to optimize or custom tailor the dosing to aparticular subject at a particular point in time. This allows for (1)improved efficacy for individual subjects, since there is variation oftherapeutic needs among subjects, and (2) improved response to variationin therapeutic needs for a given subject with time, resulting formnormal physiological variations as well as from external andenvironmental influences, such as stress, sleep deprivation, thepresence of flashing lights, alcohol intake and withdrawal, menstrualcycle, and the like The advisory algorithm may be used to characterizethe subject's susceptibility for the future seizure. If the advisoryalgorithm determines that the subject is at an elevated susceptibilityfor an epileptic seizure or otherwise predicts the onset of a seizure,the system may provide an output that indicates or otherwise recommendsor instructs the subject to take an accelerated or increased dosage of achronically prescribed pharmacological agent. Consequently, the presentinvention may be able to provide a lower chronic plasma level of the AEDand modulate the intake of the prescribed agent in order to decreaseside effects and maximize benefit of the AED.

The seizure advisory systems of the present invention may be used bymedically refractory subjects as well as by subjects who are chronicallyadministering one or more AEDs. Advantageously, such a system may beused to titrate the chronic medications to a level that reduces the sideeffects, while still providing seizure prevention effects. If theseizure advisory systems of the present invention are able to determinethat the subject has a high susceptibility with time periods that arelonger than the time for the AED to reach a threshold plasma level andprevent the onset of the seizure, the subject may be able to takesupplementary dosage of medication that is administered in response tothe assessment of the higher susceptibility to the seizure. Such amethod would reduce the subject's overall chronic intake of AEDs, whilestill preventing seizures in the subject.

The supplementary dosages may be the subject's standard dosage, a largerthan standard dosage, or a smaller than standard dosage. Thesupplementary dosage could be the same AED that the subject takeschronically, or it could be a different AED. It may be desirable to havethe dosage and/or type of medication be variable based on the ability ofthe algorithms to assess the particular subject's neurologicalcondition. While the above description focuses on subject-administeredAEDs, the systems of the present invention also encompass the use ofimplanted drug pumps that be automatically initiated by a control signalfrom the implanted assembly and/or the external assembly. Such implanteddrug pumps may use similar dosing schemes as described above.

In other embodiments, the present invention provides seizure advisorysystems in conjunction with automated or manual actuation of electricalneuromodulation. The electrical neuromodulation may be delivered to aperipheral nerve (e.g., vagus nerve stimulation (“VNS”)), a cranialnerve (e.g., trigeminal nerve stimulation (“TNS”)), directly to thebrain tissue (e.g., deep brain stimulation (DBS), cortical stimulation,etc.), or any combination thereof.

In one configuration, the seizure advisory systems of the presentinvention may be used in conjunction with an existing implantedCyberonics® VNS system. If the seizure advisory system of the presentinvention determines that the subject has transitioned to a pro-ictalcondition, the system may provide an output to the subject so as toinform the subject to activate the VNS device with a wand. Inalternative embodiments, the implanted assembly may include anintegrated pulse generator that is configured to generate theneuromodulation signal that is delivered to a vagus nerve electrode.

Advantageously, the systems and methods of the present invention may beused to reduce subject anxiety and restore a sense of control in thesubject's life, stop or reduce the duration or severity of the seizures,reduce or eliminate physical injuries to the subject, potentiallyincrease vocational opportunities by allowing epileptic subjects to holddown jobs they wouldn't otherwise be able to have, resume their drivingprivileges, increase comfort with social interaction, and enable certainkey activities of daily living.

For a further understanding of the nature and advantages of the presentinvention, reference should be made to the following description takenin conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention are set forth with particularity inthe appended claims. A better understanding of the features andadvantages of the present invention will be obtained by reference to thefollowing detailed description that sets forth illustrative embodiments,in which the principles of the invention are utilized, and theaccompanying drawings of which:

FIG. 1 illustrates one embodiment of a monitoring or data collectionsystem which comprises one or more intracranial electrodes incommunication with an external assembly through an implanted assembly.

FIG. 2 illustrates examples of electrode arrays that may be used withthe system of FIG. 1.

FIG. 3 is a simplified illustration of an implanted assembly that may beused with the system of FIG. 1.

FIG. 4 is a simplified illustration of a method of alerting a subject ofa communication error between the implanted assembly and externalassembly.

FIG. 5 is a simplified illustration of an external assembly that may beused with the system of FIG. 1.

FIG. 6 is an alternative illustration of an external assembly that maybe used with the system.

FIG. 7 illustrates an exemplary user interface including outputs of anexemplary external assembly that may be used with the system.

FIG. 8 illustrates an exemplary external assembly that may be used withthe system.

FIG. 9 is a simplified flow chart that illustrates one method of storingEEG data.

FIG. 10 illustrates a method of measuring seizure activity data forclinical and/or sub-clinical seizures.

FIG. 11 illustrates a method of evaluating efficacy of a therapy.

FIG. 12 illustrates a method of titrating an efficacious therapy.

FIG. 13 illustrates one embodiment of a simplified seizure advisorysystem which comprises an array of epidural or subdural electrodes andan array of depth electrodes in communication with an external assemblythrough an implanted assembly.

FIG. 14 schematically illustrates a plurality of algorithms that may beembodied by the present invention.

FIG. 15 illustrates a method of using a seizure advisory system.

FIG. 16 illustrates another variation to the system of FIG. 6 whichincludes a pulse generator that is coupled to a vagus nerve electrodearray.

FIG. 17 illustrates a separate vagus nerve stimulator that is used inconjunction with a seizure advisory system.

DETAILED DESCRIPTION OF THE INVENTION

Certain specific details are set forth in the following description andfigures to provide an understanding of various embodiments of theinvention. Certain well-known details, associated electronics anddevices are not set forth in the following disclosure to avoidunnecessarily obscuring the various embodiments of the invention.Further, those of ordinary skill in the relevant art will understandthat they can practice other embodiments of the invention without one ormore of the details described below. Finally, while various processesare described with reference to steps and sequences in the followingdisclosure, the description is for providing a clear implementation ofparticular embodiments of the invention, and the steps and sequences ofsteps should not be taken as required to practice this invention.

The term “condition” is used herein to generally refer to the subject'sunderlying disease or disorder—such as epilepsy, depression, Parkinson'sdisease, headache disorder, etc. The term “state” is used herein togenerally refer to calculation results or indices that are reflective acategorical approximation of a point (or group of points) along a singleor multi-variable state space continuum of the subject's condition. Theestimation of the subject's state does not necessarily constitute acomplete or comprehensive accounting of the subject's total situation.As used in the context of the present invention, state typically refersto the subject's state within their neurological condition. For example,for a subject suffering from an epilepsy condition, at any point in timethe subject may be in a different states along the continuum, such as anictal state (a state in which a neurological event, such as a seizure,is occurring), a pro-ictal state (a state in which the subject has anincreased risk of transitioning to the ictal state), an inter-ictalstate (a state in between ictal states), a contra-ictal state (a statein which the subject has a low risk of transitioning to the ictal statewithin a calculated or predetermined time period), or the like. Apro-ictal state may transition to either an ictal or inter-ictal state.

The estimation and characterization of “state” may be based on one ormore subject dependent parameters from a portion of the subject's body,such as electrical signals from the brain, including but not limited toelectroencephalogram signals and electrocorticogram signals “ECoG” orintracranial EEG (referred to herein collectively as “EEG”), braintemperature, blood flow in the brain, concentration of AEDs in the brainor blood, changes thereof, etc. While parameters that are extracted frombrain-based signals are preferred, the present invention may alsoextract parameters from other portions of the body, such as the heartrate, respiratory rate, blood pressure, chemical concentrations, etc.

An “event” is used herein to refer to a specific event in the subject'scondition. Examples of such events include transition from one state toanother state, e.g., an electrographic onset of seizure, end of seizure,or the like. For conditions other than epilepsy, the event could be anonset of a migraine headache, onset of a depressive episode, a tremor,or the like.

The occurrence of a seizure may be referred to as a number of differentthings. For example, when a seizure occurs, the subject is considered tohave exited a “pro-ictal state” and has transitioned into the “ictalstate”. However, the electrographic onset of the seizure (one event)and/or the clinical onset of the seizure (another event) have alsooccurred during the transition of states.

A subject's “susceptibility” for a seizure is a measure of thelikelihood of transitioning into the ictal state. The subject'ssusceptibility for seizure may be estimated by determining which “state”the subject is currently in. As noted above, the subject is deemed tohave an increased susceptibility for transitioning into the ictal state(e.g., have a seizure) when the subject is determined to be in apro-ictal state. Likewise, the subject may be deemed to have a lowsusceptibility for transitioning into the ictal state when it isdetermined that the subject is in a contra-ictal state.

While the discussion below focuses on measuring electrical signalsgenerated by electrodes placed near, on, or within the brain or nervoussystem (EEG signals) of subjects and subject populations for thedetermination of a subject's susceptibility for having a seizure, itshould be appreciated that the invention is not limited to measuring EEGsignals or to determining the subject's susceptibility for having aseizure. For example, the invention could also be used in systems thatmeasure one or more of a blood pressure, blood oxygenation indicatore.g. via pulse oximetry, temperature of the brain or of portions of thesubject, blood flow measurements, ECG/EKG, heart rate signals,respiratory signals, chemical concentrations of neurotransmitters,chemical concentrations of medications, pH in the blood, or otherphysiological or biochemical parameters of a subject.

Furthermore, while the remaining discussion focuses on systems andmethod for measuring a subject's susceptibility for having a seizure,the present invention may also be applicable to monitoring otherneurological or psychiatric disorders and determining the susceptibilityfor such disorders. For example, the present invention may also beapplicable to monitoring and management of sleep apnea, Parkinson'sdisease, essential tremor, Alzheimer's disease, migraine headaches,depression, eating disorders, cardiac arrhythmias, bipolar spectrumdisorders, or the like. The present invention may also be applicable tonon-medical monitoring and management of events such as storms,earthquakes, social unrest, or other episodic events from whichidentification of a low susceptibility state may be useful. As can beappreciated, the features extracted from the signals and used by thealgorithms will be specific to the underlying disorder that is beingmanaged. While certain features may be relevant to epilepsy, suchfeatures may or may not be relevant to the state measurement for otherdisorders.

The devices and systems of the present invention can be used forlong-term, ambulatory sampling and analysis of one or more physiologicalsignals, such as a subject's brain activity (e.g., EEG). In manyembodiments, the systems and methods of the present inventionincorporate brain activity analysis algorithms that extract one or morefeatures from the brain activity signals (and/or other physiologicalsignals) and classifies, or otherwise processes, such features todetermining the subject's susceptibility for having a seizure.

Some systems of the present invention may also be used to facilitatedelivery of a therapy to the subject to prevent the onset of a seizureand/or abort or mitigate a seizure. Facilitating the delivery of thetherapy may be carried out by outputting a warning or instructions tothe subject or automatically initiating delivery of the therapy to thesubject (e.g., pharmacological, electrical stimulation, focal cooling,etc.). The therapy may be delivered to the subject using an implantedassembly that is used to collect the ambulatory signals, or it may bedelivered to the subject through a different implanted or externalassembly.

A description of some systems that may be used to delivery a therapy tothe subject are described in commonly owned U.S. Pat. Nos. 6,366,813 and6,819,956, U.S. Patent Application Publication Nos. 2005/0021103(published Jan. 27, 2005), 2005/0119703 (published Jun. 2, 2005),2005/0021104 (published Jan. 27, 2005), 2005/0240242 (published Oct. 27,2005), 2005/0222626 (published Oct. 6, 2005), and U.S. patentapplication Ser. No. 11/282,317 (filed Nov. 17, 2005), Ser. Nos.11/321,897, 11/321,898, and 11/322,150 (all filed Dec. 28, 2005), thecomplete disclosures of which are incorporated herein by reference.

For subjects suspected or known to have epilepsy, the systems of thepresent invention may be used to collect data and quantify metrics forthe subjects that heretofore have not been accurately measurable. Forexample, the data may be analyzed to (1) determine whether or not thesubject has epilepsy, (2) determine the type of epilepsy, (3) determinethe types of seizures, (4) localize or lateralize one or more seizurefoci or seizure networks, (5) assess baseline seizure statistics and/orchange from the baseline seizure statistics (e.g., seizure count,frequency, duration, seizure pattern, etc.), (6) monitor forsub-clinical seizures, assess a baseline frequency of occurrence, and/orchange from the baseline occurrence, (7) measure the efficacy of AEDtreatments, deep brain or cortical stimulation, peripheral nervestimulation, and/or cranial nerve stimulation, (8) assess the effect ofadjustments of the parameters of the AED treatment, (9) determine theeffects of adjustments of the type of AED, (10) determine the effect of,and the adjustment to parameters of, electrical stimulation (e.g.,peripheral nerve stimulation, cranial nerve stimulation, deep brainstimulation (DBS), cortical stimulation, etc.), (11) determine theeffect of, and the adjustment of parameters of focal cooling (e.g., useof cooling fluids, peltier devices, etc., to diminish or reduce seizures(see, for example, “Rothman et al., “Local Cooling: A Therapy forIntractable Neocortical Epilepsy,” Epilepsy Currents, Vol. 3, No. 5,September/October 2003; pp. 153-156, (12) determine “triggers” for thesubject's seizures, (13) assess outcomes from surgical procedures, (14)provide immediate biofeedback to the subject, (15) screen subjects fordetermining if they are an appropriate candidate for a seizure advisorysystem or other neurological monitoring or therapy system, or the like.

In a first aspect of the invention, the present invention encompasses adata collection system that is adapted to collect long term ambulatorybrain activity data from the subject. In preferred embodiments, the datacollection system is able to sample one or more channels of brainactivity from the subject with one or more implanted electrodes. Theelectrodes are in wired or wireless communication with one or moreimplantable assemblies that are, in turn, in wired or wirelesscommunication with an external assembly. The sampled brain activity datamay be stored in a memory of the implanted assembly, external assemblyand/or a remote location such as a physician's computer system. Inalternative embodiments, it may be desirable to integrate the electrodeswith the implanted assembly, and such an integrated implanted assemblymay be in communication with the external assembly.

Unlike other conventional systems which have an implanted memory that isable to only store small epochs of brain activity before and after aseizure, the implantable assemblies of the present invention areconfigured to substantially continuously sample the physiologicalsignals over a much longer time period (e.g., anywhere between one dayto one week, one week to two weeks, two weeks to a month, or more) so asto be able to monitor fluctuations of the brain activity (or otherphysiological signal) over the entire time period. In alternativeembodiments, however, the implantable assembly may only periodicallysample the subject's physiological signals or selectively/aperiodicallymonitor the subject's physiological signals. Some examples of suchalternative embodiments are described in commonly owned U.S. patentapplication Ser. Nos. 11/616,788 and 11/616,793, both filed Dec. 27,2006, the complete disclosures of which are incorporated herein byreference.

When the memory is almost full, the system may provide the subject awarning so that the subject may manually initiate uploading of thecollected brain activity data or the system may automatically initiate aperiodic download of the collected brain activity data from a memory ofthe external assembly to a hard drive, flash-drive, local computerworkstation, remote server or computer workstation, or other largercapacity memory system. In alternative embodiments, the externalassembly may be configured to automatically stream the stored EEG dataover a wireless link to a remote server or database. Such a wirelesslink may use existing WiFi networks, cellular networks, pager networksor other wireless network communication protocols. Advantageously, suchembodiments would not require the subject to manually upload the dataand could reduce the down time of the system and better ensure permanentcapture of substantially all of the sampled data.

Another aspect of the invention is a system for monitoring a subject'ssusceptibility, or susceptibility, to a seizure. The system includes anelectrode and an implanted communication assembly in communication withthe electrode. The implanted communication assembly samples a neuralsignal with the electrode and substantially continuously transmits adata signal from the subject's body. The system also comprises anexternal assembly positioned outside the subject's body that isconfigured to receive and process the data signal to measure thesubject's susceptibility to having a seizure. In alternative embodimentsthe implanted assembly processes the data and measures the subject'ssusceptibility of having a seizure, in which case only data indicativeof the measured susceptibility is transmitted to the external assembly.

FIG. 1 illustrates an exemplary embodiment of a either a data collectionsystem or monitoring system as described herein. System 10 includes oneor more electrode arrays 12 that are configured to be implanted in thesubject and configured to sample electrical activity from the subject'sbrain. The electrode array 12 may be positioned anywhere in, on, and/oraround the subject's brain, but typically one or more of the electrodesare implanted within in the subject. For example, one of more of theelectrodes may be implanted adjacent or above a previously identifiedepileptic network, epileptic focus or a portion of the brain where thefocus is believed to be located. While not shown, it may be desirable toposition one or more electrodes in a contralateral position relative tothe focus or in other portions of the subject's body to monitor otherphysiological signals.

The electrode arrays 12 of the present invention may be intracranialelectrodes (e.g., epidural, subdural, and/or depth electrodes),extracranial electrodes (e.g., spike or bone screw electrodes,subcutaneous electrodes, scalp electrodes, dense array electrodes), or acombination thereof. While it is preferred to monitor signals directlyfrom the brain, it may also be desirable to monitor brain activity usingsphlenoidal electrodes, foramen ovale electrodes, intravascularelectrodes, peripheral nerve electrodes, cranial nerve electrodes, orthe like. While the remaining disclosure focuses on intracranialelectrodes for sampling intracranial EEG, it should be appreciated thatthe present invention encompasses any type of electrodes that may beused to sample any type of physiological signal from the subject.

In the configuration illustrated in FIG. 1, two electrode arrays 12 arepositioned in an epidural or subdural space, but as noted above, anytype of electrode placement may be used to monitor brain activity of thesubject. For example, in a minimally invasive embodiment, the electrodearray 12 may be implanted between the skull and any of the layers of thescalp. Specifically, the electrodes 12 may be positioned between theskin and the connective tissue, between the connective tissue and theepicranial aponeurosis/galea aponeurotica, between the epicranialaponeurosis/galea aponeurotica and the loose aerolar tissue, between theloose aerolar tissue and the pericranium, and/or between the pericraniumand the calvarium. To improve signal-to-noise ratio, such subcutaneouselectrodes may be rounded to conform to the curvature of the outersurface of the cranium, and may further include a protuberance that isdirected inwardly toward the cranium to improve sampling of the brainactivity signals. Furthermore, if desired, the electrode may bepartially or fully positioned in openings disposed in the skull.Additional details of exemplary wireless minimally invasive implantabledevices and their methods of implantation can be found in U.S.application Ser. No. 11/766,742, filed Jun. 21, 2007, the disclosure ofwhich is incorporated by reference herein in its entirety.

Some exemplary configurations of the electrode arrays 12 are shown inFIG. 2. Each of the illustrated electrode arrays has eight electrodecontacts so as to provide sixteen 16 channels for monitoring the EEGsignals. The electrode contacts may be bipolar or referential. It shouldbe appreciated however, that while FIG. 2 illustrates sixteen 16channels that are distributed over two electrode arrays, any numberelectrode arrays that have any number of contacts may be used with thepresent invention. In most embodiments, however, the system typicallyincludes between about 1 and about 256 channels, and preferably betweenabout 1 and about 32 channels, and more preferably between 8 and 32channels that are distributed over 1 array and about 4 arrays. The arraypattern and number of contacts on each array may be configured in anydesirable pattern.

FIG. 2 specifically illustrates a 2×4 grid electrode array 30, a 1×8strip electrode array 32, or a 1×8 depth electrode array 34. Each of theelectrode arrays 12 will be coupled to the implanted assembly 14 withleads 16, unless they are wireless leads. The leads of each of theelectrode arrays 12 will typically have a common lead body 17 andconnector 19. The connector 19 may take any conventional or proprietaryform, but in preferred embodiments is based on SCS/ICD technology. Theelectrode arrays could be used in either a bipolar or monopolarconfiguration.

If the system 10 includes the capability of providing stimulation of theperipheral nerve, such as the vagus nerve, the system may include avagus nerve cuff 36, which includes a modified IS1 connector that isused for Cyberonics vagus nerve lead. The systems 10 of the presentinvention may also be configured to provide electrical stimulation toother portions of the nervous system (e.g., cortex, deep brainstructures, cranial nerves, etc.). Stimulation parameters are typicallyabout several volts in amplitude, 50 microsec to 1 milisec in pulseduration, and at a frequency between about 2 Hz and about 1000 Hz.

As shown in FIG. 1, the electrode arrays 12 are in wired communicationwith an implanted assembly 14 via the wire leads 16. The individualleads from the contacts (not shown) are placed in lead 16 and the lead16 is tunneled between the cranium and the scalp and subcutaneouslythrough the neck to the implanted assembly 14. Typically, implantedassembly 14 is implanted in a sub-clavicular pocket in the subject, butthe implanted assembly 14 may be disposed somewhere else in thesubject's body. For example, the implanted assembly 14 may be implantedin the abdomen or underneath, above, or within an opening in thesubject's cranium (not shown).

Implanted assembly 14 can be used to pre-process EEG signals sampled bythe electrode array 12 and transmit a data signal that is encoded withthe sampled EEG data over a wireless link 18 to an external assembly 20,where the EEG data is permanently or temporarily stored. FIG. 3illustrates a simplified embodiment of an exemplary implanted assembly14. Implanted assembly 14 may comprise a cast epoxy packaging 40 thathermetically encapsulates the sub-assemblies of the implanted assembly14. In other embodiments, the packaging 40 may include (i) biocompatiblemetals such as platinum, niobium, titanium, tantalum, and various alloysof these metals, (ii) biocompatible ceramics such as Aluminum Oxide(Al₂O₃), Zirconium Oxide (ZO₂), and Boron Nitride (BN), (iii) and anycombination of ceramic, metal, and epoxy. Some examples of suchembodiments are described in commonly owned U.S. Patent Application No.61/017,504, filed Dec. 28, 2007, the complete disclosure of which isincorporated herein by reference.

Packaging 40 is preferably as small as possible and may have a similarpackaging footprint as a spinal cord stimulator. Thus, the packagingtypically has a volume between about 10 cubic centimeters to about 70cubic centimeters and preferably about 30 cubic centimeters, but may belarger or smaller, depending on what components are disposed therein.Packaging 40 comprises an interface 41 for the connectors 19 of leads16. The interface 41 will have at least the same number of inputchannels as the number of contacts in the electrode array, and may havemore input channels than active contacts. Interface 41 may also have oneor more bipolar output channels for delivering electrical stimulation toa peripheral nerve, brain tissue, cranial nerves, or other portions ofthe subject's body. Further details of an exemplary housing structurefor the implanted assembly can be found in U.S. Application No.61/017,504, filed Dec. 28, 2007, the disclosure of which is incorporatedby reference herein in its entirety.

The interconnections between the components of implanted assembly 14 andexternal assembly 20 may be may be wired, wireless, digital, analog, orany combination thereof, and such electronic components may be embodiedas hardware, software, firmware, or any combination thereof. While FIG.3 shows one preferred embodiment of the electronic components ofimplanted assembly 14, it should be appreciated that the functionalityperformed by each of the sub-assemblies shown in FIG. 3 may be embodiedin multiple sub-assemblies and the functionality carried out by multiplesub-assemblies of FIG. 3 may be combined into a single sub-assembly.Furthermore, some embodiments of the implanted assembly 14 may haveadditional functionalities not illustrated, while other embodiments maynot have all of the functionality and/or electronic components that areillustrated in FIG. 3.

The electronic components of the implanted assembly will typicallycomprise a signal conditioning sub-assembly 42 that conditions the oneor more EEG signals received from the interface 41. The signalconditioning sub-assembly 42 may perform amplification, combined toreduce common mode signal, filtering (e.g., lowpass, highpass, bandpass,and/or notch filtering), digital-to-analog conversion, or somecombination thereof.

The electronic components of the implanted assembly 14 may optionallycomprise dedicated circuitry and/or a microprocessor (referred to hereincollectively as “processing sub-assembly 44”) for further processing ofthe EEG signals prior to transmission to the external assembly 20. Thefurther processing may include any combination of encryption, forwarderror correction, checksum or cyclic redundancy checks (CRC), or thelike. The processing sub-assembly may comprise an ASIC, off the shelfcomponents, or the like. In one embodiment processing sub-assembly 44includes one or more multiple-core processors for processing data. Suchmultiple-core microprocessors provide faster processing, while consumingless power than multiple single core processors. Consequently, the lifeof the power source 44 may be prolonged. Some examples of suitablemultiple-core processors include the Intel® Core 2 Duo Processor and theAMD® dual-core Opteron microprocessor.

Of course, while FIG. 3 illustrates a separate conditioning assembly 42and processing sub-assembly, the two assemblies may be embodied in asingle ASIC that performs the functionality of both assemblies 42, 44.

The implanted assembly 14 will also typically include both a clock 48and a power source 50. The clock 48 is typically in the form of anoscillator and frequency synthesizer to provide synchronization and atime base for the signals transmitted from internal assembly and forsignals received from external assembly 20. Power source 50 may be anon-rechargeable battery, a rechargeable battery, a capacitor, etc. Onepreferred power source is a medical grade rechargeable Li-Ion batterythat is commonly used in other implantable devices. The rechargeablepower source 50 may also be in communication with the communicationsub-system 46 so as to receive power from outside the body by inductivecoupling, radiofrequency (RF) coupling, etc. Such rechargeable powersources typically have a lifespan of between about 3 years and about 5years. Power source 50 will generally be used to provide power to theother components of the implantable assembly 14.

In some embodiments, the implanted assembly 14 may optionally include amemory sub-system 52 (e.g., RAM) for permanently or temporarily storingor buffering the processed EEG signal. For example, memory sub-assembly52 may be used as a buffer to temporarily store the processed EEG dataif there are problems with transmitting the data to the externalassembly. For example, if the external assembly's power supply is low,the memory in the external assembly is removed, or if the externalassembly is out of communication range with the implantable assembly 14,the EEG data may be temporarily buffered in memory sub-assembly 52 andthe buffered EEG data and the current sampled EEG data may betransmitted to the external assembly when the problem has beencorrected. The buffer may be any size, but it will typically be largeenough to store between about 1 megabyte and 100 megabytes of data. Ascan be appreciated, as technology improves and the capacity of memorycards improve, it is likely that many hundreds of gigabytes or hundredsof gigabytes of data may be buffered in the internal memory. Of course,in embodiments that do not have a memory sub-system 52 in the implantedassembly 14, any data that is sampled during the times in which theexternal assembly 20 is out of communication range with the implantedassembly 14, there may simply be gaps in the stored data.

In some embodiments the system 10 of the present invention mayincorporate an alert that is activated to indicate that there is acommunication error between the implanted assembly and the externalassembly. Exemplary communication errors include, without limitation,when (1) the external assembly 20 is out of communication range with theinternal assembly 14 such that the transmitted data signals are notreceived by the external assembly, (2) there is some other error in thetransmission and receipt of data signals between the internal assembly14 and external assembly, (3) self test error has been encountered, (4)memory card is full (or nearly full), or some combination thereof.Additional exemplary causes for an alert are discussed below in the moredetailed discussion of the external assembly.

Typically, the alert is incorporated in the external assembly 20 so thatthe external assembly can provide a visual, audible, and/or tactilealert. Such an alert can indicate to the subject (or third party) thatthe external assembly 20 is not able to receive the RF signal from theimplanted assembly 14 and/or that appropriate data transfer is notoccurring. Moreover, the alert may reduce the likelihood of misplacingthe external assembly 20, since in most embodiments, once the datatransfer is interrupted, the alert may be activated by the system. Insuch a case, if the subject were to walk away from the external assembly20 (e.g., leave the external assembly 20 on a table), the subject wouldnot be advised of their susceptibility for seizure. If the subject didnot realize that they did not have their external assembly 20 with them,the subject may assume that they are in a low susceptibility and performactivities on the assumption that their external assembly 20 would warnthem of a changing to a state in which they were in a highersusceptibility to a seizure.

Additionally or alternatively, it may be possible to incorporate analert in the implanted assembly 14 and the alert may provide a tactilewarning (e.g., vibration) and/or audible alert to warn the subject thatthere is a data transmission error between the external assembly 20 andthe implanted assembly 14.

In some embodiments the external assembly can be adapted so that it willexpect to receive a data signal from the implanted assembly, and if itdoes not, the alert will be activated. The external assembly can beprogrammed to expect to receive a substantially continuous data signalfrom the implanted assembly, such that if the external assembly stopsreceiving a signal the alert will be activated. The external assemblycan also be programmed to expect to receive a data signal periodicallyrather than substantially continuously. For example, the externalassembly could expect to receive a signal every two seconds, and if itfails to receive a signal after a two second period of time, the alertwill be activated. Thus, when the external assembly is adapted to expecta data signal periodically, the alert will be activated after aspecified period of time passes without the external assembly receivingthe data signal.

In some embodiments the communication error comprises a gap in thecommunication stream. For example, if the data signal comprises anumbered sequence of packets of information, and the external assemblyreceives a signal with missing packets of information within thesequence, the alert would be activated. The implanted assembly can beadapted to temporarily store the data signal so that if the externalassembly detects a gap in the communication, the implanted assembly canattempt to retransmit the complete data signal data.

In some embodiments the communication error can include data formattingerrors. An exemplary formatting error is an invalid cyclic redundancycheck, but formatting errors as described herein include any otheralteration of data during transmission or storage.

FIG. 4 illustrates an exemplary method of activating an alert when thereis an error transmitting a data signal between the implanted assemblyand the external assembly. First, a brain signal, such as an EEG signal,is sampled from the subject at step 55. The implanted assembly thenattempts to transmit a data signal which is indicative of the brainsignal to the external assembly at step 56. If there is a communicationerror between the implanted assembly and the external assembly, step 57,the alert is activated, step 58, to notify the subject of thecommunication error. The implanted assembly can also attempt toretransmit the data signal between the implanted assembly and theexternal assembly if there is a communication error.

In some situations, the subject may be able to temporarily disable thealert and/or change the mode or parameters of the alert using a subjectinput. Such functionality may be carried out through providing a manualsubject input—such as pressing a button on the external assembly 20.

In some embodiments, external assembly 20 may be programmed to allow thesubject to disable the alert if the subject is in one or more differentneurological states. For example, if the subject is in a contra-ictalstate in which the subject is at a low susceptibility to transitioninginto an ictal state and/or a pro-ictal state in a period of time and didnot want to carry the external assembly 20 with them (e.g., to take ashower and leave the external assembly 20 in the bedroom), the subjectmay disable the alert by using the buttons 131, 133, 135 or other userinputs on the external assembly 20 (FIG. 6). The disabling of the alertcould last for a predetermined time period and then automatically bere-enabled, or the disabling of the alert may be continued until thesubject manually re-enables the alert.

The subject and/or the physician may also customize the alert parametersto the subject. For example, some subjects may want to be immediatelyalerted if there is a communication error, while others may want a timedelay before the alert is sounded.

Furthermore, if there is a prolonged alert (e.g., the subject leaves thehouse without the external assembly), the external assembly 20 mayautomatically disable the alert after a predetermined time and/or thealert may be manually disabled by a third party. To further reduce thelikelihood of misplacing the external assembly 20 and ensuring that thesubject is being monitored and advised, the external assembly 20 maycomprise a communication assembly that facilitates the wirelesscommunication with a remote party, such as the subject's caregiver,spouse, or friend (described in more detail below as the caregiveradvisory device). Thus, if an alert is sounded that indicates acommunication error, the communication assembly may send a wirelesscommunication to the remote party to alert the third party that thesubject is not being advised of their susceptibility to seizure.Typically, the wireless communication to the caregiver will be sent onlyafter a predetermined time period has elapsed.

Tuning or reprogramming of the components of implanted assembly 14 maybe carried out in vivo through communication sub-assembly 46. Forexample, the external assembly 20 and/or a dedicated programmer(controlled by physician) may be brought into communication range withthe communication sub-assembly 46 and the reprogramming instructions maybe uploaded into the processing sub-assembly.

Communication sub-assembly may include a magnetic reed switch (notshown) similar to those found in the Cyberonics® Vagus Nerve Stimulatoror spinal cord stimulators. The magnetic reed switch would enableinitiation of an electrode impedance check, self test, RAM check, ROMcheck, power supply checks, computer operating properly checks,electrode impedance check, or the like.

Implantable assembly 14 can be configured to substantially continuouslysample the brain activity of the groups of neurons in the immediatevicinity of each of the contacts in the electrode array 12. Thecommunication range between the implanted assembly 14 and the externalassembly 20 is typically about 5 meters, but could be as short asrequiring that the external assembly 20 contact the skin of the subjectand up to 10 meters, or more. Sampling of the brain activity istypically carried out at a sampling rate above about 200 Hz, andpreferably between about 200 Hz and about 1000 Hz, and most preferablybetween about 400 Hz and about 512 Hz, but it could be higher or lower,depending on the specific condition being monitored, the subject, andother factors. Each sample of the subject's brain activity willtypically contain between about 8 bits per sample and about 32 bits persample, and preferably between about 12 bits and 16 bits per sample. Thewireless communication link 18 may have an overall data transfer ratebetween approximately 5 Kbits/sec and approximately 500 Kbits/sec, andpreferably about approximately 50 kbits/sec. As can be appreciated, theover air data transfer rate of the implanted assembly could beconsiderably higher (e.g., 2 Mbits/sec), which would allow for a lowertransmit duty cycle which will result in power savings.

For example, if each communication transmission to the external assemblyincludes one EEG sample per transmission, and the sample rate is 400 Hzand there are 16 bits/sample, the data transfer rate from theimplantable assembly 14 to the external assembly 20 is at least about6.4 Kbits/second/channel. If there are 16 channels, the total datatransfer rate for the wireless communication link 18 between theimplanted assembly 14 and the external assembly 20 would be about 102Kbits/second.

While substantially continuous sampling and transmission of brainactivity is preferred, in alternative embodiments, it may be desirableto have the implantable assembly 14 sample the brain activity of thesubject in a non-continuous basis or the sampling rate may vary over theperiod of monitoring. In such embodiments, the implantable assembly 14may be configured to sample the brain activity signals periodically(e.g., a burst of sampling every 5 seconds) or aperiodically. Forexample, it may be desirable to reduce or increase the sampling ratewhen a subject has gone to sleep.

To enable the high data transfer rates of the present invention, thewireless communication link 18 provided by the communicationsub-assembly 46 is typically in the form of an electromagneticradiofrequency communication link. Conventional devices typically use aslower communication link (e.g., that is designed for low data transferrates and long link access delays) and transmit data out on anon-continuous basis. In contrast, the present invention uses a fastaccess communication link that transmits smaller bursts of data (e.g.,single or small number of EEG samples from each of the channels at atime) on a substantially continuous basis so as to allow forsubstantially real-time analysis of the EEG data. The radiofrequencyused to transfer data between the implantable assembly 14 and externalassembly 20 is at a frequency typically between 13.56 MHz and 10 GHz,preferably between about 900 MHz and about 2.4 GHz, more preferably atabout 2.4 GHz, or between about 900 MHz and about 928 MHz. Onepotentially useful communication sub-assembly is a 900 MHz ISM telemetrytransmitter. If it is desired to avoid FCC regulations, it may bedesirable to use telemetry at low frequency, such as below 9 Khz.

As can be appreciated, while the aforementioned frequencies are thepreferred frequencies, the present invention is not limited to suchfrequencies and other frequencies that are higher and lower may also beused. For example, it may be desirable us use the MICS (Medical ImplantCommunication Service band) that is between 402-405 MHz to facilitatethe communication link.

In order to facilitate data transmission from the implanted assembly 14to the external assembly 20, the antennas 47 and 62 of the implantableassembly 14 and external assembly 14, respectively, must be maintainedin communication range of each other. The frequency used for thewireless communication link has a direct bearing on the communicationrange. Typically, the communication range is typically at least onefoot, preferably between about one foot and about twenty feet, and morepreferably between about six feet and sixteen feet. As can beappreciated, however, the present invention is not limited to suchcommunication ranges, and larger or smaller communication ranges may beused. For example, if an inductive communication link is used, thecommunication range will be smaller than the aforementioned range; butif higher frequencies are used, the communication range may be largerthan twenty feet.

While not illustrated in FIGS. 1 to 4, the systems 10 of the presentinvention may also make use of conventional or proprietary forward errorcorrection (“FEC”) methods to control errors and ensure the integrity ofthe data transmitted from the implantable assembly 14 to the externalassembly 20. Such forward error correction methods may include suchconventional implementations such as cyclic redundancy check (“CRC”),checksums, or the like.

In some situations, instead of a wireless link between the implantedassembly 14 and the external assembly 20, it may be desirable to have awire running from the subject-worn data collection assembly 20 to aninterface (not shown) that could directly link up to the implantedassembly 14 that is positioned below the subject's skin. For example,the interface may take the form of a magnetically attached transducer,as with cochlear implants. This could enable higher rates of datatransmission between the implanted assembly 14 and the external assembly20.

FIG. 5 illustrates a simplified embodiment of external assembly 20. Forexample, in alternative embodiments the functionality performed by asingle sub-assembly shown in FIG. 5 may be embodied in multiplesub-assemblies, and/or the functionality carried out by multiplesub-assemblies of FIG. 5 may be combined into a single sub-assembly.Furthermore, other embodiments of the external assembly 20 may haveadditional functionalities not illustrated, while other embodiments maynot have all of the functionality and/or electronic components that areillustrated in FIG. 5. External assembly 20 is typically portable andcomprises a housing 60 that is of a size that allows for storage in apurse or pocket of the subject. The handheld housing 60 typically has aform factor of a MP3 player (e.g., Apple iPod), cellular phone, personaldigital assistant (PDA), pager, or the like. In some embodiments, thecomponents of the external assembly 20 may be integrated within ahousing of such consumer electronics devices.

FIGS. 6, 7, and 8 illustrate alternative embodiments of externalassembly 20.

The illustrated external assembly shows a user interface 72 thatincludes a variety of indicators for providing system status and alertsto the subject. User interface 72 may include one or more indicators 101that indicate the subject's brain state. In the illustrated embodiment,the output includes light indicators 101 (for example, LEDs) thatcomprise one or more (e.g., preferably two or more) discrete outputsthat differentiate between a variety of different brain states. In theillustrated embodiment, the brain state indicators 101 include a redlight 103, yellow/blue light 105, and a green light 107 for indicatingthe subject's different brain states (described more fully below). Insome configurations the lights may be solid, blink or provide differentsequences of flashing to indicate different brain states. If desired,the light indicators may also include an “alert” or “information” light109 that is separate from the brain state indicators so as to minimizethe potential confusion by the subject.

External assembly 20 may also include a liquid crystal display (“LCD”)111 or other display for providing system status outputs to the subject.The LCD 111 generally displays the system components' status and promptsfor the subject. For example, as shown in FIG. 7, LCD 111 can displayindicators, in the form of text or icons, such as, for example,implantable device battery strength 113, external assembly batterystrength 115, and signal strength 117 between the implantable device andthe external assembly 20. If desired, the LCD may also display thealgorithm output (e.g., brain state indication) and the user interface72 may not require the separate brain state indicator(s) 101. The outputon the LCD is preferably continuous, but in some embodiments may appearonly upon the occurrence of an event or change of the system statusand/or the LCD may enter a sleep mode until the subject activates a userinput. LCD 111 is also shown including a clock 119, audio status 121(icon shows PAD is muted), and character display 123 for visual textalerts to the subject—such as an estimated time to seizure or anestimated “contra-ictal” time. While not shown in FIG. 7, the LCD 111may also indicate the amount of free memory remaining on the memorycard.

FIGS. 8_(a)-8_(g) illustrate a variety of different views of anotherembodiment of the external assembly. FIGS. 8_(a) and 8_(b) are twoalternative top plan views of the external assembly. FIGS. 8_(c) and8_(e) are opposing side views. FIG. 8_(d) is a back view. FIG. 8_(f) isa front view. FIG. 8_(g) is a bottom view. The illustrated embodiment ofFIG. 8 is a pager-style external assembly that may be carried on a clip(not shown) that may be used to couple the external assembly to thesubject's belt or bag. The typical dimensions of this embodiment of theexternal assembly are typically 1.00″×2.50″×3.50″, but may be larger orsmaller as desired.

Similar to the other embodiments, the external assembly of FIG. 8comprises a plurality of user inputs 131, 133, 135, brain stateindicators 101 and outputs that indicate a state of the system (e.g.,LCD 111). As shown in FIG. 8_(b) , the LCD may comprise a plurality ofdifferent icons on the LCD 111 to indicate the state of the system. Forexample, the illustrated embodiment includes an external assemblybattery indicator 115, implanted device battery indicator 113, telemetrysignal strength indicator 117, volume indicator 121, and a memory cardstatus indicator 6. To differentiate between the implanted device systemstate and external assembly system state, it may be desirable to providea physical separation 7 between the icons. The physical separationelement 7 could be a physical barrier that overlays the LCD, twoseparate LCDs that are spaced from each other, or simply a discernableseparation between icons on the LCD.

The LCD 111 and brain state indicators 101 are typically viewable by thesubject when it is attached to the subject's belt. As such, the subjectneed only glance down onto the top surface of the PAD when an audible ortactile indication is provided that indicates a subject's brain state orchange thereof.

In the embodiment of FIG. 8_(a) , the brain state indicators 103, 105,107 may be positioned along the junction of the top surface and frontsurface so as to be viewable from multiple angles. In another embodimentshown in FIG. 8_(b) , either in addition to the brain state indicators103, 105, 107 on the front surface (FIG. 8_(f) ) or as an alternative tothe brain state indicator on the front surface, the top surface may havebrain state indicators 103′, 105′, 107′ that are viewable from the topsurface. In the embodiment shown in 8 _(b), the brain state indicators103′, 105′, 107′ on the top surface may be different colored anddifferent shaped to further differentiate between the different brainstates. In both embodiments of FIGS. 8_(a) and 8_(b) the acknowledgementinput 135 may be positioned along a top surface of the external assemblyso that the acknowledgement input 135 is readily accessible to thesubject when the brain state indicator 101 is activated.

The front surface of the external assembly may also comprise a door 9that houses the removable data card an on/off input button (not shown).When opened, the subject may replace the full (or defective) data cardwith a new card. Alternatively, if the subject desires to turn on or offthe external assembly, the subject may activate the on/off input.Typically, the subject will keep the external assembly on at all times,but in instances which require the external assembly to be off (e.g., onan airplane), the subject may have the ability to turn off the externalassembly and stop the transmission of the data signal from the implanteddevice—which may help to conserve battery power of the external assemblyand implanted device.

Referring again to FIG. 6, external assembly 20 may also include aspeaker 125 and a pre-amp circuit to provide audio outputs to thesubject (e.g., beeps, tones, music, recorded voice alerts, etc.) thatmay indicate brain state or system status to the subject. User interface72 may also include a vibratory output device 127 and a vibration motordrive 129 to provide a tactile alert to the subject, which may be usedseparately from or in conjunction with the visual and audio outputsprovided to the subject. The vibratory output device 127 is generallydisposed within external assembly 20, and is described in more detailbelow. Depending on the desired configuration any of the aforementionedoutputs may be combined to provide information to the subject.

The external assembly 20 preferably comprises one or more subject inputsthat allow the subject to provide inputs to the external assembly. Inthe illustrated embodiment, the inputs comprise one or more physicalinputs (e.g., buttons 131, 133, 135) and an audio input (in the form ofa microphone 137 and a pre-amp circuit).

Similar to conventional cellular phones, the inputs 131, 133, 135 may beused to toggle between the different types of outputs provided by theexternal assembly. For example, the subject can use buttons 133 tochoose to be notified by tactile alerts such as vibration rather thanaudio alerts (if, for example, a subject is in a movie theater). Or thesubject may wish to turn the alerts off altogether (if, for example, thesubject is going to sleep). In addition to choosing the type of alert,the subject can choose the characteristics of the type of alert. Forexample, the subject can set the audio tone alerts to a low volume,medium volume, or to a high volume.

Some embodiments of the external assembly 20 will allow for recordingaudio, such as voice data. A dedicated voice recording user input 131may be activated to allow for voice recording. In preferred embodiments,the voice recording may be used as an audio subject seizure diary. Sucha diary may be used by the subject to record when a seizure hasoccurred, when an aura or prodrome has occurred, when a medication hasbeen taken, to record subject's sleep state, stress level, etc. Suchvoice recordings may be time stamped and stored in data storage of theexternal assembly and may be transferred along with recorded EEG signalsto the physician's computer. Such voice recordings may thereafter beoverlaid over the EEG signals and used to interpret the subject's EEGsignals and improve the training of the subject's customized algorithm,if desired.

The one or more inputs may also be used to acknowledge system statusalerts and/or brain state alerts. For example, if the external assemblyprovides an output that indicates a change in brain state, one or moreof the LEDs 101 may blink, the vibratory output may be produced, and/oran audio alert may be generated. In order to turn off the audio alert,turn off the vibratory alert and/or to stop the LEDs from blinking, thesubject may be required to acknowledge receiving the alert by actuatingone of the user inputs (e.g., button 135).

While the external assembly is shown having inputs 131, 133, 135, anynumber of inputs may be provided on the external assembly. For example,in one alternate embodiment, the external assembly may comprise only twoinput buttons. The first input button may be a universal button that maybe used to scroll through output mode options. A second input button maybe dedicated to voice recording. When an alert is generated by theexternal assembly, either of the two buttons may be used to acknowledgeand deactivate the alert. In other embodiments, however, there may be adedicated user input for acknowledging the alerts.

External assembly 20 may comprise a main processor 139 and a complexprogrammable logic device (CPLD) 141 that control much of thefunctionality of the external assembly. In the illustratedconfiguration, the main processor and/or CPLD 141 control the outputsdisplayed on the LCD 111, generates the control signals delivered to thevibration device 127 and speaker 125, and receives and processes thesignals from buttons 131, 133, 135, microphone 137, and a real-timeclock 149. The real-time clock 149 may generate the timing signals thatare used with the various components of the system.

The main processor may also manage a data storage device 151, providesredundancy for a digital signal processor 143 (“DSP”), and manage thetelemetry circuit 147 and a charge circuit 153 for a power source, suchas a battery 155.

While main processor 139 is illustrated as a single processor, the mainprocessor may comprise a plurality of separate microprocessors,application specific integrated circuits (ASIC), or the like.Furthermore, one or more of the microprocessors 139 may include multiplecores for concurrently processing a plurality of data streams.

The CPLD 141 may act as a watchdog to the main processor 139 and the DSP143 and may flash the LCD 111 and brain state indicators 101 if an erroris detected in the DSP 143 or main processor 139. Finally, the CPLD 141controls the reset lines for the main microprocessor 139 and DSP 143.

A telemetry circuit 147 and antenna may be disposed in the PAD 10 tofacilitate one-way or two-way data communication with the implanteddevice. The telemetry circuit 147 may be an off the shelf circuit or acustom manufactured circuit. Data signals received from the implanteddevice by the telemetry circuit 147 may thereafter be transmitted to atleast one of the DSP 143 and the main processor 139 for furtherprocessing.

The DSP 143 and DRAM 145 receive the incoming data stream from thetelemetry circuit 147 and/or the incoming data stream from the mainprocessor 139. The brain state algorithms process the data (for example,EEG data) and estimate the subject's brain state, and are preferablyexecuted by the DSP 143 in the PAD. In other embodiments, however, thebrain state algorithms may be implemented in the implanted device, andthe DSP may be used to generate the communication to the subject basedon the data signal from the algorithms in the implanted device.

The main processor 139 is also in communication with the data storagedevice 151. The data storage device 151 preferably has at least about 7GB of memory so as to be able to store data from about 8 channels at asampling rate of between about 200 Hz and about 1000 Hz. With suchparameters, it is estimated that the 7 GB of memory will be able tostore at least about 1 week of subject data. Of course, as theparameters (e.g., number of channels, sampling rate, etc.) of the datamonitoring change, so will the length of recording that may be achievedby the data storage device 151. Furthermore, as memory capacityincreases, it is contemplated that the data storage device will belarger (e.g., 10 GB or more, 20 GB or more, 50 GB or more, 100 GB ormore, etc.). Examples of some useful types of data storage deviceinclude a removable secure digital card or a USB flash key, preferablywith a secure data format.

“Subject data” may include one or more of raw analog or digital EEGsignals, compressed and/or encrypted EEG signals or other physiologicalsignals, extracted features from the signals, classification outputsfrom the algorithms, etc. The data storage device 151 can be removedwhen full and read in card reader 157 associated with the subject'scomputer and/or the physician's computer. If the data card is full, (1)the subsequent data may overwrite the earliest stored data or (2) thesubsequent data may be processed by the DSP 143 to estimate thesubject's brain state (but not stored on the data card). While preferredembodiments of the data storage device 151 are removable, otherembodiments of the data storage device may comprise a non-removablememory, such as FLASH memory, a hard drive, a microdrive, or otherconventional or proprietary memory technology. Data retrieval off ofsuch data storage devices 151 may be carried out through conventionalwired or wireless transfer methods.

The power source used by the external assembly may comprise any type ofconventional or proprietary power source, such as a non-rechargeable orrechargeable battery 155. If a rechargeable battery is used, the batteryis typically a medical grade battery of chemistries such as a lithiumpolymer (LiPo), lithium ion (Li-Ion), or the like. The rechargeablebattery 155 will be used to provide the power to the various componentsof the external assembly through a power bus (not shown). The mainprocessor 139 may be configured to control the charge circuit 153 thatcontrols recharging of the battery 155.

In addition to being able to communicate with the implanted device, theexternal assembly may have the ability to communicate wirelessly with aremote device—such as a server, database, physician's computer,manufacturer's computer, or a caregiver advisory device (all of whichcan be herein referred to as “CAD”). In the exemplary embodiment, theexternal assembly may comprise a communication assembly (not shown) incommunication with the main processor 139 that facilitates the wirelesscommunication with the remote device. The communication assembly may bea conventional component that is able to access a wireless cellularnetwork, pager network, wifi network, or the like, so as to be able tocommunicate with the remote device. The wireless signal could betransfer of data, an instant message, an email, a phone call, or thelike.

In one particular embodiment, the external assembly is able to deliver asignal through the communication assembly that is received by the CAD soas to inform the caregiver of the subject's brain state or change inbrain state. The CAD would allow the caregiver to be away from thesubject (and give the subject independence), while still allowing thecaregiver to monitor the subject's brain state and susceptibility forseizure. Thus, if the subject's brain state indicates a highsusceptibility for a seizure or the occurrence of a seizure, thecaregiver would be notified via the CAD, and the caregiver couldfacilitate an appropriate treatment to the subject (e.g., small dosageof an antiepileptic drug, make the subject safe, etc.). A signal may beprovided to the caregiver only if the subject has a high susceptibilityfor a seizure or if a seizure is detected, or it may provide the sameindications that are provided to the subject.

In yet other embodiments, the communication assembly could be used toinform the caregiver that there is a communication error between thesubject's implanted assembly and external assembly, so as to indicatethat the subject is not being properly monitored and advised. Such acommunication would allow the caregiver to intervene and/or inform thesubject that they are not being monitored.

In other embodiments, the communication assembly could be used tofacilitate either real-time or non-real time data transfer to the remoteserver or database. If there is real time transfer of data, such aconfiguration could allow for remote monitoring of the subject's brainstate and/or EEG signals. Non-real time transfer of data could expeditetransfer and analysis of the subject's recorded EEG data, extractedfeatures, or the like. Thus, instead of waiting to upload the brainactivity data from the subject's data storage device, when the subjectvisits their physician, the physician may have already had theopportunity to review and analyze the subject's transferred brainactivity data prior to the subject's visit.

The external assembly may be configured to perform a selfhardware/software test to detect system errors—such as power failures,software failures, impedance change, battery health of the implanteddevice and external assembly, internal clock and voltage reference,hardware (processors, memory, and firmware) checks, or the like. Theself test may be performed periodically, upon initial startup, upon asystem reset, or some combination thereof. The system preferably runs aself-test on the external assembly, implanted device, electrode arrayand the communication links. The external assembly may emit a toneand/or display information on the LCD at the initiation of theself-test(s). If the external assembly, implanted device, electrodearray and/or communication link pass the self-test, the subject may benotified with an alert indicating the respective devices passed theself-test. If any of the components do not pass the self-test, thesubject can be alerted with an output that indicates which component didnot pass (for example, an icon on the LCD representing the componentwhich did not pass the test flashes). There may also be an audio alert,such as a voice alert, that one or some of the devices failed the test.The external assembly may also indicate these failures with informationor alert light 109 (FIG. 7). The system may then wait for input from thesubject to acknowledge the system failure(s) by depressing a button onthe external assembly (such as the “OK” button 135 in FIG. 6), whichindicates the user is aware of the alert. Additionally or alternatively,there may be a text display on the LCD notifying the subject to contactthe manufacturer or physician to receive further instructions.

The external assembly may be configured to be toggled between two ormore different modes of operation. In one embodiment, the physician maytoggle the external assembly between three different modes ofoperations. Of course, it should be appreciated that the externalassembly may have as little as one mode of operation, or more than threedifferent modes of operations.

In one example, a first mode of operation of the external assembly maybe merely data collection, in which data signals from the implanteddevice are stored in the data storage 151 of the external assembly. Insuch a mode, the user interface 72 may be modified to only providesystem status indications to the subject via the LCD 111, and the brainstate indicators 101 may be temporarily disabled.

In a second mode of operation, after the brain state algorithms havebeen trained on the subject's data that was collected during the firstmode of operation, the brain state algorithms may be implemented toprocess substantially real-time data signals and the brain stateindicators 101 may be enabled so as to inform the subject of theirsubstantially real-time brain state.

In a third mode of operation, it may be desirable to only receive andprocess the data signals from the implanted device, but no longer storethe substantially continuous data signals in a memory of the externalassembly. For example, if the brain state algorithms are performing asdesired, the brain data signals from the implanted device will not haveto be stored and analyzed. Consequently, the subject would not have toperiodically replace the data card as frequently. However, it may stillbe desirable to store the data signals that immediately precede andfollow any detected seizure. Consequently, in the third mode suchseizure data signals may optionally be stored.

As noted above, in some embodiments the system comprises one or morebrain state algorithms. In one embodiment, the brain state algorithmsembodied in the present invention will generally characterize thesubject's brain state as either “Low Susceptibility,” “Unknown,”“Elevated Susceptibility” or “Detection.” It is intended that these aremeant to be exemplary categories and are in no way to be limiting andadditional brain states or fewer brain state indicators may be provided.There may be different types of algorithms which are configured tocharacterize the brain state into more or less discrete states.“Contra-ictal” generally means that brain activity indicates that thesubject has a low susceptibility to transition to an ictal state and/ora pro-ictal state for an upcoming period of time (for example, 60minutes to 90 minutes). This is considered positive information and nouser lifestyle action is required. A pro-ictal state generally meansthat the algorithm(s) in the PAD are determining that the subject has anelevated susceptibility for a seizure (possibly within a specified timeperiod). A “detection” state generally means that brain activityindicates that the subject has already transitioned into an ictal state(e.g., occurrence of an electrographic seizure) or that there is animminent clinical seizure. User actions should be focused on safety andcomfort. An “unknown” state generally means the current type of brainactivity being monitored does not fit within the known boundaries of thealgorithms and/or that the brain activity does not fit within thecontra-ictal state, pro-ictal state, or ictal state. Therefore noevaluation can be reliably made. “Unknown” can also indicate there hasbeen a change in the status of the brain activity and while the subjectdoes not have an elevated susceptibility and no seizure has beendetected, it is not possible to reliable tell the subject that they maynot transition into an ictal state and/or pro-ictal state for a periodof time. This state is considered cautionary and requires somecautionary action such as limiting exposure to risk. The two differenttypes of “unknown” may have separate brain state indicators, or they maybe combined into a single brain state indicator, or the user interfacemay not provide the “unknown” state to the subject at all.

The external assembly preferably comprises visual indicators, such asLEDs, notifying the subject of the determined brain state. In onepreferred embodiments, the visual indicators for the brain state alertswill comprise a green, yellow/blue, and red lights. The green light willbe illuminated when the PAD determines that the brain state is in a “lowsusceptibility to seizure” state. The yellow or blue light will beilluminated when the subject is in an “unknown” state. The PAD will emita solid red light when the subject is in the “high susceptibility”state. The PAD will emit a blinking red light when the subject is in the“detection” state. The light colors or number of light indicators arenot intended to be limiting. Any color may be used. It may be desirableto include additional lights or colors (e.g., orange) to furtherdelineate the subject's estimated condition. In yet other embodiments,it may be desirable to display only a green light and red light.

Further exemplary details of external assembly 20 can be found in U.S.Provisional Application No. 60/952,463, filed Jul. 27, 2007, thedisclosure of which is incorporated by reference herein in its entirety.

FIG. 9 illustrates an exemplary simplified method embodied by thepresent invention. In use, the implantable assembly 14 samples the brainactivity signals with the active contacts on the electrode array 12(step 80). The sampled brain activity signals are transmitted to theimplantable assembly 14 over leads 16 (but this can also be donewirelessly). The implantable assembly 14 may then pre-process thesampled brain activity signals as desired (step 82), and then use thecommunication sub-assembly to transmit a substantially continuouswireless RF signal to the external assembly 20 that is encoded with EEGdata (step 84). The RF signal emitted by the internal assembly 14 isreceived by an antenna in the external assembly, and the RF signal isdecoded to extract the EEG data (step 86). The sampled EEG data maythereafter be stored in a memory of the external assembly 20 (step 88).Rather than storing the data in a memory in the external assembly (step88), the data can also be transmitted to a remote device in substantialreal time without storage in the external assembly.

In preferred embodiments, the wireless signal is transmittedsubstantially immediately after sampling of the EEG signal to allow forsubstantially continuous real-time transfer of the subject's EEG data tothe external assembly 20. In alternate embodiments, however, the RFsignal with the encoded EEG data may be temporarily buffered in aninternal memory 52 (FIG. 4) of the implanted assembly 14 and thecommunication transmission to the external assembly 20 may be delayed byany desired time period and such transmissions may include the bufferedEEG data and/or a real-time sampled EEG data.

Instead of sending large packets of stored data with each RFcommunication transmission, the methods and devices of the presentinvention substantially continuously sample physiological signals fromthe subject and communicate in real-time small bits of data during eachRF signal communication to the external assembly. Of course, forembodiments in which real-time data transfer is not needed, it may bedesirable to transmit larger packets of data to the external assembly 20using the communication link, and such a communication protocol is alsoencompassed by the present invention.

As noted above, the data signals that are wirelessly transmitted fromimplanted assembly 14 may be encrypted so as to help ensure the privacyof the subject's data prior to transmission to the external assembly 20.Alternatively, the data signals may be transmitted to the externalassembly 20 with unencrypted EEG data, and the EEG data may be encryptedprior to the storage of the EEG data in the memory of external assembly20 or prior to transfer of the stored EEG data to the local computerworkstation 22 or remote server 26.

The download of brain activity data may be manually carried out by thesubject or automatically initiated by a component of system 10. After atime period of collecting EEG data (e.g., one day to one week, one weekto two weeks, two weeks to one month, etc.), the external assembly 20may be manually put in communication with a local computer workstation22 through either a wireless link or wired link to download the storeddata to a memory of the local computer workstation 22. For example, inone embodiment, a wired USB 2.0 connection (improvements thereof orother conventional interface) may be used to upload the stored EEG datato the local computer workstation 22. Alternatively, instead ofdownloading the data directly to a local or remote computer workstation22, 26, the data may be downloaded to a portable hard drive or flashdrive for temporary storage. In such embodiments, the drive maythereafter be brought or delivered into the physician's office fordownload and analysis.

Furthermore, as shown in FIG. 1, the communication sub-assembly ofexternal assembly 20 may have the capability to continuously orperiodically communicate wirelessly with a broadband, high speedcommunication network 24—such as a cellular network, pager network, theInternet (Wifi, WiMAX), or the like, to automatically and wirelesslytransmit the stored and/or real-time data over the network 24 to aremote server (not shown) or remote computer workstation 26.

For example, the local computer workstation 22 (or remote computerworkstation 26) may periodically command the external assembly to uploadthe data from the memory of the external assembly, or the externalassembly may be programmed to automatically upload the EEG dataaccording to a predetermined schedule or upon reaching a threshold levelmemory usage. By incrementally downloading days or weeks of stored brainactivity data periodically, the subject's physician may be able to startanalysis of the brain activity data and possibly complete the analysisof the long term data prior to the subject going to the physician'soffice. If a subject were to bring in a week or month of stored brainactivity data for analysis by the physician, the subject would have towait hours, days or even weeks for the analysis of the data to becompleted. Consequently, instead of waiting for the analysis, analysisof the data may be substantially completed and therapy or diagnosisdecisions may be made prior to the office visit and the subject would beable to immediately implement any changes or start therapy immediatelyafter visiting the office.

Once implanted in the subject, the systems 10 of the present inventionmay be used for a variety of different data collection and monitoringpurposes. For example, in one usage the systems of the present inventionmay be used to quantify seizure activity statistics for the subject.Currently, the most common method of quantifying a subject's seizureactivity is through subject self reporting using a seizure diary.However, it has been estimated that up to 63% of all seizures are missedby subjects. Subject's missing the seizures are usually caused by thesubjects being amnesic to the seizures, unaware of the seizures,mentally incapacitated, the seizures occur during sleep, or the like.FIG. 10 illustrates a simplified method 90 of measuring a subject'sseizure activity statistics. At step 92, the electrode arrays 12, leads16 (or can be wireless), and implanted assembly 14 are implanted in thesubject. At step 94, the implanted assembly is activated tosubstantially continuously sample EEG signals from the subject. At step96, the sampled EEG signals are wirelessly transmitted from theimplanted assembly 14 to an external assembly 20. At step 98, thesampled EEG signals are stored in a memory—either in the externalassembly 20 or in one of the computer workstations 22, 26. At step 100,the stored EEG signals are manually analyzed by the physician and/oranalyzed with EEG analysis software, typically using a seizure advisoryalgorithm(s) or spike detector, to derive statistics for the clinicalseizures and/or the sub-clinical seizures for the subject based on thelong-term, ambulatory EEG data. For example, the following statisticsmay be quantified using the present invention:

Seizure count over a time period—How many clinical and sub-clinicalseizures does the subject have in a specific time period?

Seizure frequency—How frequent does the subject have seizures? What isthe seizure frequency without medication and with medication? Withoutelectrical stimulation and with electrical stimulation?

Seizure duration—How long do the seizures last? Without medication andwith medication? Without electrical stimulation and with electricalstimulation?

Seizure timing—When did the subject have the seizure? Do the seizuresoccur more frequently at certain times of the day?

Seizure patterns—Is there a pattern to the subject's seizures? Aftercertain activities are performed? What activities appear to triggerseizures for this particular subject?

Finally, at step 102, report generation software may be used to generatea report based on the statistics for the seizure activity. The reportmay include some or all of the statistics described above, and may alsoinclude the EEG signal(s) associated with one or more of the seizures.The report may include text, graphs, charts, images, or a combinationthereof so as to present the information to the physician and/or subjectin an actionable format.

As noted above, the present invention enables the quantification,documentation and long term monitoring of sub-clinical seizures in asubject. Because the subject is unaware of the occurrence ofsub-clinical seizures, heretofore the long term monitoring ofsub-clinical seizures was not possible. Documentation of thesub-clinical seizures may further provide insight into the relationshipbetween sub-clinical seizures and clinical seizures, may provideimportant additional information relevant to the effectiveness ofsubject therapy, and may further enhance the development of additionaltreatments for epilepsy.

FIG. 11 illustrates one exemplary method of how the seizure activitydata may be used to evaluate the efficacy or clinical benefit of acurrent or potential therapy and allow for the intelligent selection ofan appropriate therapy for an individual subject or stopping the usageof ineffective therapies. Currently, effectiveness of the AED therapy isbased on self-reporting of the subject, in which the subject makesentries in a diary regarding the occurrence of their seizure(s). If theentries in the subject diary indicate a reduction in seizure frequency,the AED is deemed to be effective and the subject continues with someform of the current regimen of AEDs. If the subject entries in thesubject diary do not indicate a change in seizure frequency, the AEDsare deemed to be ineffective, and typically another AED isprescribed—and most often in addition to the AED that was deemed to beineffective. Because AEDs are typically powerful neural suppressants andare associated with undesirable side-effects, the current methodology ofassessing the efficacy of the AEDs often keeps the subject onineffective AEDs and exposes the subject to unnecessary side-effects.

By way of example, a medically refractory subject coming to an epilepsycenter for the first time might first have the system of the presentinvention implanted and then asked to collect data for a prescribed timeperiod, e.g., 30 days. The initial 30 days could be used to establish abaseline measurement for future reference. The physician could thenprescribe an adjustment to the subject's medications and have thesubject collect data for another time period, e.g., an additional 30 dayperiod. Metrics from this analysis could then be compared to theprevious analysis to see if the adjustment to the medications resultedin an improvement. If the improvement was not satisfactory, the subjectcan be taken off of the unsatisfactory medication, and a new medicationcould be tried. This process could continue until a satisfactory levelof seizure control was achieved. The present invention provides a metricthat allows physicians and subjects to make informed decisions on theeffectiveness and non-effectiveness of the medications.

FIG. 11 schematically illustrates this method 110. At step 114, theimplantable assembly and external assembly are used to monitor thesubject's EEG to obtain a baseline measurement for the subject. Thebaseline measurement is typically seizure activity statistics for aspecific time period (e.g., number of seizures, seizure duration,seizure pattern, seizure frequency, etc.). It should be appreciatedhowever, that the baseline measurement may include any number of typesof metrics. For example, the baseline metric may include univariate,bivariate, or multivariate features that are extracted from the EEG, orthe like. In one preferred embodiment, the baseline measurement isperformed while the subject is not taking any AEDs or using any othertherapy. In other embodiments, however, the subject may be taking one ormore AEDs and the baseline measurement will be used to evaluateadjustments to dosage or other add-on therapies.

At step 116, the therapy that is to be evaluated is commenced. Thetherapy will typically be an AED and the subject will typically haveinstructions from the neurologist, epileptologist, or drug-manufacturerregarding the treatment regimen for the AED. The treatment regimen maybe constant (e.g., one pill a day) throughout the evaluation period, orthe treatment regimen may call for varying of some parameter of thetherapy (e.g., three pills a day for the first week, two pills a day forthe second week, one pill a day for the third week, etc.) during theevaluation period. During the evaluation period, the implantableassembly and external assembly will be used to substantiallycontinuously sample the subject's EEG. The sampled EEG may thereafter beprocessed to obtain a follow-up measurement for the subject (Step 118).If the baseline measurement was seizure statistics for the baseline timeperiod, then the follow-up measurement will be the corresponding seizurestatistics for the evaluation period. At step 120, the baselinemeasurement is compared to the follow-up measurement to evaluate thetherapy. If the comparison indicates that the therapy did notsignificantly change the subject's baseline, the therapy may be stopped,and other therapies may be tried.

Currently, the primary metric in evaluating the efficacy of an AED iswhether or not the AED reduces the subject's seizure count. In additionto seizure count, the systems of the present invention would be able totrack any reduction in seizure duration, modification in seizurepatterns, reduction in seizure frequency, or the like. While seizurecount is important, because the present invention is able to providemuch greater detail than just seizure count, efficacy of an AED may bemeasured using a combination of additional metrics, if desired. Forexample, if the subject was having a large number of sub-clinicalseizures, spike bursts, or other epileptiform activity (which thesubject was not aware of) and the AED was effective in reducing orstopping the sub-clinical seizures, the systems of the present inventionwould be able to provide metrics for such a situation. With conventionalsubject diary “metrics”, the subject and physician would not be aware ofsuch a reduction, and such an AED would be determined to benon-efficacious for the subject. However, because the present inventionis able to provide metrics for the sub-clinical seizures, theefficacious medication could be continued.

At step 122, the epileptologist or neurologist may decide to change oneor more parameters of the therapy. For example, they may change adosage, frequency of dosage, form of the therapy or the like, andthereafter repeat the follow-up analysis for the therapy with thechanged parameter. After the “second” follow up measurement is complete,the second follow up data may be obtained and thereafter compared to the“first” follow up measurements and/or the baseline measurements.

Of course, the therapy is not limited to AED therapy. Therapies that canbe assessed by the present invention can include cooling therapy,electrical stimulation (such as vagus nerve stimulation, deep brainstimulation, cortical stimulation), or the like. The present inventionmay be used to screen the subject's for determining appropriate therapyfor their condition and/or to determine the appropriate parameters forthe selected therapy.

In addition to evaluating an efficacy of a therapy for an individualsubject, the metrics that are provided by the present invention alsoenable an intelligent titration of a subject's medications. As shown inFIG. 12, if the subject is on a treatment regimen of an efficacioustherapy, the present invention may be used to reduce/titrate a dosage orfrequency of intake of the AED (or AEDs) 130. Typically, the subjectwill already be on a treatment regimen of the efficacious therapy, butif not, the efficacious therapy is commenced with the prescribedparameters, e.g., “standard” dosage (Step 134). At step 136, thesubject's EEG (and/or other physiological signal) is monitored for adesired time period to obtain a first subject data measurement for thesubject (e.g., the baseline measurement). Similar to previousembodiments, the first subject data measurement may be any desiredmetrics, but will typically be selected from clinical seizure frequency,clinical seizure duration, sub-clinical seizure frequency, sub-clinicalseizure duration, medication side effects. At step 138, after thebaseline measurement has been taken, the first efficacious therapy isstopped and a therapy with at least one changed parameter is started(referred to as “therapy with second parameters” in FIG. 12). Typically,the changed parameter will be a reduction in dosage, but it could bechanging a frequency of the same dosage, a change in formulation or formof the same AED, or the like.

At step 140, the subject's EEG is monitored and processed to obtain asecond subject data measurement for the subject (e.g., follow-up datameasurement). If the neurologist or epileptologist is satisfied with theresults, the titration may end. But in many embodiments, the titrationprocess will require more than one modification of parameters of thetherapy. In such embodiments, the second therapy is stopped (step 142),and a therapy with N^(th) parameters (e.g., third, fourth, fifth . . . )is commenced (step 144). Monitoring and processing of the subject's EEGsignals are repeated (step 146), and the process is repeated a desirednumber of times (as illustrated by arrow 147). Once the desired numbersof modifications to the therapy have been made, the various subject datameasurements may be analyzed and compared to each other to determine themost desirous parameters for the therapy (step 148).

With the instrumentation provided by the present invention, the processof selecting appropriate AEDs and the dosages of such AEDs could occurmuch faster and with much greater insight than ever before. Further, thechance of a subject remaining on an incremental AED that was providinglittle incremental benefit would be minimized. Once a subject was undercontrol, the subject could cease the use of the system, but theimplantable assembly could remain. In the future, the subject might beasked to use the system again should their condition change.

In addition to or as an alternative to the above data collection uses,the systems 10 of the present invention may be used to analyze EEG datasubstantially in real-time and provide an output to the subject and/orprovide a therapy to the subject based on the analysis of the EEG data.In preferred embodiments, the systems of the present invention may beused as seizure advisory systems that measure the subject'ssusceptibility to a seizure and/or to detect the onset of the seizureprior to the clinical manifestation of the seizure and provide anappropriate warning to the subject.

The platform of system 10 used for data collection (described above) andthe system used for determining the subject's susceptibility for havinga seizure will generally have the same general components, so that thesame system may be used for both data collection and advising ofsusceptibility to seizure. However, when the system is used for datacollection during a training period, the algorithms that determine thesubject's susceptibility of having a seizure may be disabled or not yetprogrammed in the system so as to not be accessible to the subject. Ifand when seizure advising is desired, such algorithms may be enabledand/or added into the system.

For example, EEG data may be collected as noted above. The collected EEGdata may be analyzed off-line (e.g., in a separate computer, such asworkstation 22) and, if desired, algorithms may be customized orotherwise tuned to the subject specific EEG data. Thereafter, theparameters of the disabled algorithm(s) may be modified or the entiretuned algorithm may be uploaded to a memory of system 10 and the aspectsof the system relevant to seizure advising may be enabled. Finally, theseizure advising functionality in the system 10 may be enabled and usedby the subject in real-time on a substantially continuous basis.

FIG. 13 illustrates an embodiment of the seizure advisory system inwhich the electrode array 12 includes at least one depth electrodearray, but otherwise contains similar components as the system ofFIG. 1. Typically, the depth electrode will be only for sampling EEGsignals, but as will be described below, the electrode arrays 12 may beused to deliver electrical stimulation directly to the brain. The system10 shown in FIGS. 1 and 13 will include algorithms that process the EEGin substantially real-time to determine the subject's susceptibility forhaving a seizure. When a high susceptibility to a seizure is determined,a user interface of the external assembly 20 will provide an output tothe subject that is indicative of the high susceptibility to theseizure. In the illustrated embodiment, the output to the subject may bea visual display on the LCD, a light display on the LED, a vibratorysignal, and/or an audio output, etc., as described above.

FIG. 14 depicts an example of the overall structure of a system forperforming substantially real-time assessment of the subject's brainactivity and for determining the communication output that is providedto the subject. The system may comprise one or more algorithms ormodules that process input data 162. The algorithms may take a varietyof different forms, but typically comprises one or more featureextractors 164 a, 164 b, 165 and at least one classifier 166 and 167.The embodiment illustrated in FIG. 14 shows a contra-ictal algorithm 163and a pro-ictal algorithm 161 which share at least some of the samefeature extractors 164 a and 164 b. In alternative embodiments, however,the algorithms used in the system may use exactly the same featureextractors or completely different feature extractors.

The input data 162 is typically EEG, but may comprise representations ofphysiological signals obtained from monitoring a subject and maycomprise any one or combination of the aforementioned physiologicalsignals from the subject. The input data may be in the form of analogsignal data or digital signal data that has been converted by way of ananalog to digital converter (not shown). The signals may also beamplified, preprocessed, and/or conditioned to filter out spurioussignals or noise. For purposes of simplicity the input data of all ofthe preceding forms is referred to herein as input data 162. In onepreferred embodiment, the input data comprises between about 1 channeland about 64 channels of EEG from the subject.

The input data 162 from the selected physiological signals is suppliedto the one or more feature extractors 164 a, 164 b, 165. Featureextractor 164 a, 164 b, 165 may be, for example, a set of computerexecutable instructions stored on a computer readable medium, or acorresponding instantiated object or process that executes on acomputing device. Certain feature extractors may also be implemented asprogrammable logic or as circuitry. In general, feature extractors 164a, 164 b, 165 can process data 162 and identify some characteristic ofinterest in the data 162. Such a characteristic of the data is referredto herein as an extracted feature.

Each feature extractor 164 a, 164 b, 165 may be univariate (operating ona single input data channel), bivariate (operating on two datachannels), or multivariate (operating on multiple data channels). Someexamples of potentially useful characteristics to extract from signalsfor use in determining the subject's propensity for a neurologicalevent, include but are not limited to, bandwidth limited power (alphaband [8-13 Hz], beta band [13-18 Hz], delta band [0.1-4 Hz], theta band[4-8 Hz], low beta band [12-15 Hz], mid-beta band [15-18 Hz], high betaband [18-30 Hz], gamma band [30-48 Hz], high frequency power [>48 Hz],bands with octave or half-octave spacings, wavelets, etc.), second,third and fourth (and higher) statistical moments of the EEG amplitudesor other features, spectral edge frequency, decorrelation time, Hjorthmobility (HM), Hjorth complexity (HC), the largest Lyapunov exponentL(max), effective correlation dimension, local flow, entropy, loss ofrecurrence LR as a measure of non-stationarity, mean phase coherence,conditional probability, brain dynamics (synchronization ordesynchronization of neural activity, STLmax, T-index, angularfrequency, and entropy), line length calculations, first, second andhigher derivatives of amplitude or other features, integrals, andmathematical linear and non-linear operations including but not limitedto addition, subtraction, division, multiplication and logarithmicoperations. Of course, for other neurological conditions, additional oralternative characteristic extractors may be used with the systemsdescribed herein.

The extracted characteristics can be supplied to the one or moreclassifiers 166, 167. Like the feature extractors 164 a, 164 b, 165,each classifier 166, 167 may be, for example, a set of computerexecutable instructions stored on a computer readable medium or acorresponding instantiated object or process that executes on acomputing device. Certain classifiers may also be implemented asprogrammable logic or as circuitry.

The classifiers 166, 167 analyze one or more of the extractedcharacteristics, and either alone or in combination with each other (andpossibly other subject dependent parameters), provide a result 168 thatmay characterize, for example, a subject's condition. The output fromthe classifiers may then be used to determine the subject'ssusceptibility for having a seizure, which can determine the outputcommunication that is provided to the subject regarding their condition.As described above, the classifiers 166, 167 are trained by exposingthem to training measurement vectors, typically using supervised methodsfor known classes, e.g. ictal, and unsupervised methods as describedabove for classes that can't be identified a priori, e.g. contra-ictal.Some examples of classifiers include k-nearest neighbor (“KNN”), linearor non-linear regression, Bayesian, mixture models based on Gaussians orother basis functions, neural networks, and support vector machines(“SVM”). Each classifier 166, 167 may provide a variety of outputresults, such as a logical result or a weighted result. The classifiers166, 167 may be customized for the individual subject and may be adaptedto use only a subset of the characteristics that are most useful for thespecific subject. Additionally, over time, the classifiers 166, 167 maybe further adapted to the subject, based, for example, in part on theresult of previous analyses and may reselect extracted characteristicsthat are used for the specific subject.

For the embodiment of FIG. 14, the pro-ictal classifier 167 may classifythe outputs from feature extractors 164 a, 164 b to detectcharacteristics that indicate that the subject is at an elevatedsusceptibility for a neurological event, while the contra-ictalclassifier 166 may classify the outputs from feature extractors 164 a,164 b, 165 to detect characteristics that occur when the subject isunlikely to transition into an ictal condition for a specified period oftime. The combined output of the classifiers 166, 167 may be used todetermine the output communication provided to the subject. Inembodiments which comprise only the contra-ictal algorithm, the outputfrom the contra-ictal classifier 166 alone may be used to determine theoutput communication to the subject. Further details of exemplaryalgorithms that may be used to identify a subject's susceptibility tohaving a seizure may be found in U.S. Provisional Patent Application No.60/897,549, filed Jan. 25, 2007, to Snyder et al., entitled “Systems andMethods for Identifying a Contra-ictal Condition in a Subject” andco-pending application Ser. No. 12/020,450, filed on Jan. 25, 2008,titled “Systems and Methods for Identifying a Contra-Ictal Condition ina Subject”, the complete disclosures of which are incorporated herein byreference.

Depending on the specific feature extractors and classifiers used, thecomputational demands of the analysis provided by feature extractors 164a, 164 b, 165 and classification provided by classifiers 166, 167 can beextensive. In the case of ambulatory systems supplied by portable powersources, such as batteries, supplying the power required to meet thecomputational demands can severely limit power source life. In preferredembodiments, both the seizure advisory algorithm are embodied in theexternal assembly 20. Processing the EEG data with the algorithms in theexternal assembly 20 provides a number of advantages over having thealgorithms in the implanted assembly. First, keeping the processing inthe external assembly 20 will reduce the overall power consumption inthe implanted assembly 14 and will prolong the battery life of theimplanted assembly 14. Second, charging of battery or replacing thebattery of the external assembly 20 is much easier to accomplish. Thebattery of the external assembly may be charged by placing the externalassembly 20 in a recharging cradle (e.g., inductive recharging) orsimply by attaching the external assembly to an AC power source. Third,customizing, tuning and/or upgrading the algorithms will be easier toachieve in the external assembly 20. Such changes may be carried out bysimply connecting the external assembly to the physician's computerworkstation 20 and downloading the changes. Alternatively, upgrading maybe performed automatically over a wireless connection with thecommunication sub-assembly 64.

While it is preferred to have the observer algorithms 160 in theexternal assembly 20, in alternate embodiments of the present invention,the observer algorithms 160 may be wholly embodied in the implantedassembly 14 or a portion of one or more of the observer algorithms 160may be embodied in the implanted assembly 14 and another portion of theone or more algorithms may be embodied in the external assembly 20. Insuch embodiments, the processing sub-assembly 44 (or equivalentcomponent) of the implanted assembly 14 may execute the analysissoftware, such as a seizure advisory algorithm(s) or portions of suchalgorithms. For example, in some configurations, one or more cores ofthe processing sub-assembly 44 may run one or more feature extractorsthat extract features from the EEG signal that are indicative of thesubject's susceptibility to a seizure, while the classifier could run ona separate core of the processing sub-assembly 44. Once the feature(s)are extracted, the extracted feature(s) may be sent to the communicationsub-assembly 46 for the wireless transmission to the external assembly20 and/or store the extracted feature(s) in memory sub-system 52 of theimplanted assembly 14. Because the transmission of the extractedfeatures is likely to include less data than the EEG signal itself, sucha configuration will likely reduce the bandwidth requirements for thewireless communication link 18 between the implantable assembly 14 andthe external assembly 20.

In other embodiments, the seizure advisory algorithms may be whollyembodied within the implanted assembly 14 and the data transmission tothe external assembly 29 may include the data output from theclassifier, a warning signal, recommendation, or the like. A detaileddiscussion of various embodiments of the internal/external placement ofsuch algorithms are described in commonly owned U.S. patent applicationSer. No. 11/322,150, filed Dec. 28, 2005 to Bland et al., and U.S.Provisional Patent Application No. 60/805,710, filed Jun. 23, 2006, thecomplete disclosures of which are incorporated herein by reference.

FIG. 15 illustrates a method of using the systems described herein tocollect data, tune the algorithms and use the tuned algorithms toestimate the subject's susceptibility to a seizure. At step 200, thesubject is implanted with the system 10 in which the seizure advisoryalgorithms are disabled or not yet present in the system. The userinterface aspects that are related to the seizure advising may also bedisabled.

At step 202, the system is used to collect EEG data for a desired timeperiod, as described in detail above. Generally, the desired time periodwill be a specified time period such as at least one week, between oneweek and two weeks, between two weeks and one month, between one monthand two months, or two months or more. But the desired time period maysimply be a minimum time period that provides a desired number ofseizure events. At step 204, the collected EEG data may be periodicallydownloaded to the physician's computer workstation or the entire EEGdata may be brought into the physician's office in a single visit.

At step 206, the physician may analyze the EEG data using the computerworkstation that is running EEG analysis software, the EEG data may betransferred to a remote analyzing facility that comprises a multiplicityof computing nodes where the EEG data may be analyzed on an expeditedbasis, or it may even be possible to analyze the EEG analysis softwarein the external assembly 20. Analysis of the EEG data may be performedin a piecewise fashion after the shorter epochs of EEG data is uploadedto the database, or the analysis of the EEG data may be started afterthe EEG data for the entire desired time period has been collected.Typically, “analysis of the EEG data” will include identifying andannotating at least some of spike bursts, the earliest electrographicchange (EEC), unequivocal electrical onset (UEO), unequivocal clinicalonset (UCO), electrographic end of seizure (EES). Identification of suchevents may be performed automatically with a seizure detectionalgorithm, manually by board certified epileptologists, or a combinationthereof. After the EEG data is annotated, the seizure advisoryalgorithm(s) may be trained on the annotated EEG data in order to tunethe parameters of the algorithm(s) to the subject specific EEG data.

Once the algorithm(s) are tuned to meet minimum performance criteria, atstep 208 the tuned algorithm(s) or the parameter changes to the basealgorithm may be uploaded to the external assembly 20. At step 210, thetuned algorithm and the other user interface aspects of the presentinvention may be activated, and the observer algorithm may be used bythe subject to monitor the subject's susceptibility to a seizure and/ordetect seizures.

When the seizure advisory system 10 determines that the subject is at anincreased susceptibility to a seizure (or otherwise detects a seizure),the external assembly may be configured to generate a seizure warning tothe subject, as described above. For example, the external assembly mayactivate a red or yellow LED light, generate a visual warning on theLCD, provide an audio warning, deliver a tactile warning, or anycombination thereof. If desired, the warning may be “graded” so as toindicate the confidence level of the seizure advisory, indicate theestimated time horizon until the seizure, or the like. “Grading” of thewarning may be through generation of different lights, audio, or tactilewarning or a different pattern of lights, audio or tactile warnings.

Additionally or alternatively, the external assembly may include aninstruction to the subject regarding an appropriate therapy forpreventing or reducing the susceptibility for the seizure. Theinstruction may instruct the subject to take a dosage of theirprescribed AED, perform biofeedback to prevent/abort the seizure,manually activate an electrical stimulator (e.g., use a wand to activatean implanted VNS device) or merely to instruct the subject to makethemselves safe. A more complete description of various instructionsthat may be output to the subject are described in commonly owned,copending U.S. patent application Ser. Nos. 11/321,897 and 11/321,898,both of which are incorporated by reference herein.

The outputs provided to the subject via the external assembly may be astandardized warning or instruction, or it may be programmed by thephysician to be customized specifically to the subject and theircondition. For example, different subjects will be taking differentAEDs, different dosages of the AEDs, and some may be implanted withmanually actuatable stimulators (e.g., NeuroPace RNS, Cyberonics VNS,etc.), and the physician will likely be desirous to customize thetherapy to the subject. Thus, the physician will be able to program thewarning and/or instruction to correspond to the level of susceptibility,estimated time horizon to seizure, or the like.

The systems 10 of the present invention may also be adapted to provideclosed-loop therapy to the subject. FIG. 16 illustrates one embodimentof the system 10 that includes therapy delivery assembly in theimplanted assembly 14. The system 10 illustrated in FIG. 16 willgenerally have the same components as shown in FIGS. 1 and 13, but willalso include an implanted pulse generator (not shown) that is incommunication with a vagus nerve cuff electrode 220 via a lead 222. Whenthe seizure advisory system determines that the subject is at anelevated susceptibility to a seizure, the system may automaticallyinitiate delivery of electrical stimulation to the vagus nerve cuffelectrode. The parameters (e.g., burst/no burst mode, amplitude, pulsewidth, pulse frequency, etc.) of the electrical stimulation may bevaried based on the subject's susceptibility, or the parameter may beconstant.

While not shown in FIG. 16, the present invention further embodies othertherapy outputs—such as electrical stimulation of the brain tissue(e.g., deep brain structures, cortical stimulation) using electrodearray 12 or other electrode arrays (not shown), stimulation of cranialnerves (e.g., trigeminal stimulation), delivery of one or more drugs viaimplanted drug dispensers, cryogenic therapy to the brain tissue,cranial nerves, and/or peripheral nerves), or the like. Similar to vagusnerve stimulation, parameters of the therapy may be constant or theparameters of the therapy may be modified based on the subject'sestimated susceptibility.

Such therapies may be used in addition to the vagus nerve stimulation oras an alternative to such therapy. If desired, the type of therapydelivered to the subject may be modified based on the subject'ssusceptibility. For example, if the elevated susceptibility estimates along time horizon until seizure and/or a lower confidence level, a morebenign type of therapy (e.g., electrical stimulation) may be employed.But if the elevated susceptibility estimates a shorter time horizonuntil seizure and/or has a higher confidence level, a different type oftherapy (e.g., pharmacotherapy) may be employed.

FIG. 17 illustrates an embodiment of the present invention that is usedwith an existing open loop Cyberonics vagus nerve stimulator 300. Whenthe system 10 of the present invention determines that the subject is atan elevated risk for a seizure, the system 10 may generate acommunication to the subject via the external assembly 20, and thesubject may use a wand associated with the vagus nerve stimulator 300 tomanually active stimulation of the vagus nerve.

Some embodiments of the monitoring system may include an integralsubject diary functionality. The subject diary may be a module in theexternal assembly and inputs by the subject may be used to providesecondary inputs to provide background information for the sampled EEGsignals. For example, if a seizure is recorded, the seizure diary mayprovide insight regarding a trigger to the seizure, or the like. Thediary may automatically record the time and date of the entry by thesubject. Entries by the subject may be a voice recording, or throughactivation of user inputs on the external assembly. The diary may beused to indicate the occurrence of an aura, occurrence of a seizure, theconsumption of a meal, missed meal, delayed meal, activities beingperformed, consumption of alcohol, the subject's sleep state (drowsy,going to sleep, waking up, etc.), mental state (e.g., depressed,excited, stressed), intake of their AEDs, medication changes, misseddosage of medication, menstrual cycle, illness, or the like. Thereafter,the subject inputs recorded in the diary may also be used by thephysician in assessing the subject's epilepsy state and/or determine theefficacy of the current treatment. Furthermore, the physician may beable to compare the number of seizures logged by the subject to thenumber of seizures detected by the seizure detection algorithm.

While preferred embodiments of the present invention have been shown anddescribed herein, it will be obvious to those skilled in the art thatsuch embodiments are provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the invention. It should be understoodthat various alternatives to the embodiments of the invention describedherein may be employed in practicing the invention. For example, thepresent invention also encompasses other more invasive embodiments whichmay be used to monitor the subject's neurological system.

It is intended that the following claims define the scope of theinvention and that methods and structures within the scope of theseclaims and their equivalents be covered thereby.

What is claimed is:
 1. A system for monitoring neurological signals in apatient, the system comprising: an implantable sensor adapted to collectneurological signals; an implantable assembly configured to sample theneurological signals collected by the sensor, wherein said implantableassembly comprises: a physical memory configured to store or buffer saidneurological signals; a first telemetry circuit; a processingsubassembly configured to process neurological signals prior totransmission to a rechargeable communication device external to thepatient's body; and the rechargeable communication device external tothe patient's body comprising: a display configured to indicate aneurological state of the patient; a second telemetry circuit; aprocessor configured to control outputs on the display and manage thesecond telemetry circuit, at least one of the outputs providing anindication of a change in a brain state of the patient; and wherein saidrechargeable communication device is configured to wirelesslycommunicate with the implantable assembly and to transmit acommunication error alert to a caregiver advisory device in an event ofa communication error between the implantable assembly and therechargeable communication device, wherein the caregiver advisory deviceallows at least one of monitoring the patient or facilitating treatment.2. The system of claim 1, further comprising the caregiver advisorydevice, wherein the rechargeable communication device is configured towirelessly communicate with the caregiver advisory device.
 3. The systemof claim 2, wherein the caregiver advisory device is configured toindicate if there is a communication error between the rechargeablecommunication device and the implantable assembly.
 4. The system ofclaim 2, wherein the caregiver advisory device is configured to providea visible alert if there is a communication error between therechargeable communication device and the implantable assembly.
 5. Thesystem of claim 2, wherein the caregiver advisory device is configuredto provide an audible alert if there is a communication error betweenthe rechargeable communication device and the implantable assembly. 6.The system of claim 1, wherein the communication error comprises afailure of the rechargeable communication device to receive an expecteddata signal from the implantable assembly.
 7. The system of claim 1,wherein the communication error comprises a failure of the rechargeablecommunication device to receive a data signal from the implantableassembly for a predetermined amount of time.
 8. The system of claim 1,wherein the communication error comprises a failure of the rechargeablecommunication device to receive a data signal from the implantableassembly at an expected time or within an expected period of time. 9.The system of claim 1, wherein the communication error comprises amissing packet of data in a numbered sequence of packets transmittedfrom the implantable assembly to the rechargeable communication device.10. The system of claim 1, wherein the rechargeable communication deviceis configured to automatically deactivate the communication error alertafter a predetermined period of time.
 11. The system of claim 1, whereinthe implantable sensor is adapted to collect neurological signals frominside the patient's skull.
 12. The system of claim 1, wherein theimplantable sensor is adapted to collect neurological signals from alocation between the patient's skull and at least a layer of thepatient's scalp.
 13. The system of claim 1, wherein the rechargeablecommunication device is configured to receive the neurological signalsfrom the implantable assembly.
 14. The system of claim 1, wherein therechargeable communication device is configured to communicate with thecaregiver advisory device via a wireless cellular network.
 15. Thesystem of claim 1, wherein the rechargeable communication device isconfigured to communicate with the caregiver advisory device via a phonecall.
 16. The system of claim 1, wherein the implantable assembly isconfigured to transmit the neurological signals to the rechargeablecommunication device substantially immediately after sampling.
 17. Amethod of monitoring neurological signals in a patient, comprising:collecting neurological signals using a sensor implanted in the patient;sampling the neurological signals using an implantable assembly; storingor buffering said neurological signals in memory of the implantedassembly; processing said neurological signals prior to transmission toan external rechargeable communication device using a processorsubassembly; displaying a neurological state of the patient using therechargeable communication device; controlling outputs on therechargeable communication device, at least one of the outputs providingan indication of a change in a brain state of the patient and managing atelemetry circuit using a processor on said rechargeable communicationdevice; indicating a change in brain state of the patient based on theneurological signals via an output on said rechargeable communicationdevice; wirelessly transmitting a communication error alert from therechargeable communication device external to the patient's body to acaregiver advisory device in the event of a communication error betweenthe implantable assembly and the rechargeable communication devicewherein the caregiver advisory device allows for at least one ofmonitoring the patient or facilitating treatment.
 18. The method ofclaim 17, further comprising wirelessly communicating from therechargeable communication device to the caregiver advisory device. 19.The method of claim 18, further comprising generating an indication fromthe caregiver advisory device if there is a communication error betweenthe rechargeable communication device and the implantable assembly. 20.The method of claim 18, further comprising providing a visible alertfrom the caregiver advisory device if there is a communication errorbetween the rechargeable communication device and the implantableassembly.
 21. The method of claim 18, further comprising providing avisible alert from the caregiver advisory device if there is acommunication error between the rechargeable communication device andthe implantable assembly.
 22. The method of claim 17, wherein saidcommunication error comprises a failure of the rechargeablecommunication device to receive an expected data signal from theimplantable assembly.
 23. The method of claim 17, wherein saidcommunication error comprises a failure of the rechargeablecommunication device to receive a data signal from the implantableassembly for a predetermined amount of time.
 24. The method of claim 17,wherein said communication error comprises a failure of the rechargeablecommunication device to receive a data signal from the implantableassembly at an expected time or within an expected period of time. 25.The method of claim 17, wherein said communication error comprises amissing packet of data in a numbered sequence of packets transmittedfrom the implantable assembly to the rechargeable communication device.26. The method of claim 17, further comprising automaticallydeactivating the communication error alert after a predetermined periodof time.
 27. The method of claim 17, wherein said collectingneurological signals comprises collecting neurological signals frominside the patient's skull.
 28. The method of claim 17, wherein saidcollecting neurological signals comprises collecting neurologicalsignals from a location between the patient's skull and at least a layerof the patient's scalp.
 29. The method of claim 17, further comprisingreceiving at the rechargeable communication device the neurologicalsignals from the implantable assembly.
 30. The method of claim 17,wherein said transmitting the communication error alert comprisestransmitting the communication error alert from the rechargeablecommunication device to the caregiver advisory device via a wirelesscellular network.
 31. The method of claim 17, wherein said transmittingthe communication error alert comprises transmitting the communicationerror alert from the rechargeable communication device to the caregiveradvisory device via a phone call.
 32. The method of claim 17, furthercomprising transmitting the neurological signals from the implantableassembly to the rechargeable communication device substantiallyimmediately after sampling.